reinforcement learning for finance yves hilpisch

Author Yves Hilpisch, founder and CEO of The Python Quants, provides the background you need in concise fashion. ML practitioners, financial traders, portfolio managers, strategists, and analysts will focus on the implementation of these algorithms in the form of self-contained Python code and the application to important financial problems.

Objev podobné jako Reinforcement Learning for Finance - Yves Hilpisch

Written for developers with some understanding of deep learning algorithms. Experience with reinforcement learning is not required. Grokking Deep Reinforcement Learning introduces this powerful machine learning approach, using examples, illustrations, exercises, and crystal-clear teaching. You''ll love the perfectly paced teaching and the clever, engaging writing style as you dig into this awesome exploration of reinforcement learning fundamentals, effective deep learning techniques, and practical applications in this emerging field. We all learn through trial and error. We avoid the things that cause us to experience pain and failure. We embrace and build on the things that give us reward and success. This common pattern is the foundation of deep reinforcement learning: building machine learning systems that explore and learn based on the responses of the environment. • Foundational reinforcement learning concepts and methods • The most popular deep reinforcement learning agents solving high-dimensional environments • Cutting-edge agents that emulate human-like behavior and techniques for artificial general intelligence Deep reinforcement learning is a form of machine learning in which AI agents learn optimal behavior on their own from raw sensory input. The system perceives the environment, interprets the results of its past decisions and uses this information to optimize its behavior for ... Unknown localization key: "more"

Objev podobné jako Grokking Deep Reinforcement Learning - Miguel Morales

The significantly expanded and updated new edition of a widely used text on reinforcement learning, one of the most active research areas in artificial intelligence.Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives while interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the field''s key ideas and algorithms. This second edition has been significantly expanded and updated, presenting new topics and updating coverage of other topics.Like the first edition, this second edition focuses on core online learning algorithms, with the more mathematical material set off in shaded boxes. Part I covers as much of reinforcement learning as possible without going beyond the tabular case for which exact solutions can be found. Many algorithms presented in this part are new to the second edition, including UCB, Expected Sarsa, and Double Learning. Part II extends these ideas to function approximation, with new sections on such topics as artificial neural networks and the Fourier basis, and offers expanded treatment of off-policy learning and policy-gradient methods. Part III has ... Unknown localization key: "more"

Objev podobné jako Reinforcement Learning - Andrew G. Barto, Richard S. Sutton

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Humans learn best from feedback—we are encouraged to take actions that lead to positive results while deterred by decisions with negative consequences. This reinforcement process can be applied to computer programs allowing them to solve more complex problems that classical programming cannot. Deep Reinforcement Learning in Action teaches you the fundamental concepts and terminology of deep reinforcement learning, along with the practical skills and techniques you’ll need to implement it into your own projects. Key features • Structuring problems as Markov Decision Processes • Popular algorithms such Deep Q-Networks, Policy Gradient method and Evolutionary Algorithms and the intuitions that drive them • Applying reinforcement learning algorithms to real-world problems Audience You’ll need intermediate Python skills and a basic understanding of deep learning. About the technology Deep reinforcement learning is a form of machine learning in which AI agents learn optimal behavior from their own raw sensory input. The system perceives the environment, interprets the results of its past decisions, and uses this information to optimize its behavior for maximum long-term return. Deep reinforcement learning famously contributed to the success of AlphaGo but that’s not all it can do! Alexander Zai is a Machine Learning Engineer at Amazon AI working on ... Unknown localization key: "more"

Objev podobné jako Deep Reinforcement Learning in Action - Alexander Zai, Brandon Brown

In just a few years, deep reinforcement learning (DRL) systems such as DeepMinds DQN have yielded remarkable results. This hybrid approach to machine learning shares many similarities with human learning: its unsupervised self-learning, self-discovery of strategies, usage of memory, balance of exploration and exploitation, and its exceptional flexibility. Exciting in its own right, DRL may presage even more remarkable advances in general artificial intelligence. Deep Reinforcement Learning in Python: A Hands-On Introduction is the fastest and most accessible way to get started with DRL. The authors teach through practical hands-on examples presented with their advanced OpenAI Lab framework. While providing a solid theoretical overview, they emphasize building intuition for the theory, rather than a deep mathematical treatment of results. Coverage includes: Components of an RL system, including environment and agents Value-based algorithms: SARSA, Q-learning and extensions, offline learning Policy-based algorithms: REINFORCE and extensions; comparisons with value-based techniques Combined methods: Actor-Critic and extensions; scalability through async methods Agent evaluation Advanced and experimental techniques, and more How to achieve breakthrough machine learning performance by combining deep neural networks with reinforcement learning Reduces the learning curve by relying on the authors’ OpenAI Lab framework: requires less upfront theory, math, and programming expertise Provides ... Unknown localization key: "more"

Objev podobné jako Foundations of Deep Reinforcement Learning - Laura Graesser, Wah Loon Keng

Deep reinforcement learning has attracted considerable attention recently. Impressive results have been achieved in such diverse fields as autonomous driving, game playing, molecular recombination, and robotics. In all these fields, computer programs have taught themselves to understand problems that were previously considered to be very difficult. In the game of Go, the program AlphaGo has even learned to outmatch three of the world''s leading players.Deep reinforcement learning takes its inspiration from the fields of biology and psychology. Biology has inspired the creation of artificial neural networks and deep learning, while psychology studies how animals and humans learn, and how subjects'' desired behavior can be reinforced with positive and negative stimuli. When we see how reinforcement learning teaches a simulated robot to walk, we are reminded of how children learn, through playful exploration. Techniques that are inspired by biology and psychology work amazingly well in computers: animal behavior and the structure of the brain as new blueprints for science and engineering. In fact, computers truly seem to possess aspects of human behavior; as such, this field goes to the heart of the dream of artificial intelligence. These research advances have not gone unnoticed by educators. Many universities have begun offering courses ... Unknown localization key: "more"

Objev podobné jako Deep Reinforcement Learning - Aske Plaat

Reinforcement learning (RL) will deliver one of the biggest breakthroughs in AI over the next decade, enabling algorithms to learn from their environment to achieve arbitrary goals. This practical book shows data science and AI professionals how to perform the reinforcement process that allows a machine to learn by itself.

Objev podobné jako Reinforcement Learning - Phil Winder Ph.D.

This book is an introduction to stochastic analysis and quantitative finance; it includes both theoretical and computational methods. Topics covered are stochastic calculus, option pricing, optimal portfolio investment, and interest rate models. Also included are simulations of stochastic phenomena, numerical solutions of the Black-Scholes-Merton equation, Monte Carlo methods, and time series. Basic measure theory is used as a tool to describe probabilistic phenomena. The level of familiarity with computer programming is kept to a minimum. To make the book accessible to a wider audience, some background mathematical facts are included in the first part of the book and also in the appendices. This work attempts to bridge the gap between mathematics and finance by using diagrams, graphs and simulations in addition to rigorous theoretical exposition. Simulations are not only used as the computational method in quantitative finance, but they can also facilitate an intuitive and deeper understanding of theoretical concepts. Stochastic Analysis for Finance with Simulations is designed for readers who want to have a deeper understanding of the delicate theory of quantitative finance by doing computer simulations in addition to theoretical study. It will particularly appeal to advanced undergraduate and graduate students in mathematics and business, but not excluding ... Unknown localization key: "more"

Objev podobné jako Stochastic Analysis for Finance with Simulations - Geon Ho Choe

A complete resource for finance students, this textbook presents the most common empirical approaches in finance in a comprehensive and well-illustrated manner that shows how econometrics is used in practice, and includes detailed case studies to explain how the techniques are used in relevant financial contexts. Maintaining the accessible prose and clear examples of previous editions, the new edition of this best-selling textbook provides support for the main industry-standard software packages, expands the coverage of introductory mathematical and statistical techniques into two chapters for students without prior econometrics knowledge, and includes a new chapter on advanced methods. Learning outcomes, key concepts and end-of-chapter review questions (with full solutions online) highlight the main chapter takeaways and allow students to self-assess their understanding. Online resources include extensive teacher and student support materials, including EViews, Stata, R, and Python software guides.

Objev podobné jako Introductory Econometrics for Finance - Chris Brooks

Help students move from surface-level learning to the transfer of understanding. How do social studies teachers maximize instruction to ensure students are prepared for an informed civic life? VISIBLE LEARNING® for Social Studies, Grades K-12 shows how the field is more than simply memorizing dates and facts—it encapsulates the skillful ability to conduct investigations, analyze sources, place events in historical context, and synthesize divergent points of view. The Visible Learning framework demonstrates that learning is not an event, but rather a process in which students move from surface-level learning to deep learning, and then onto the transfer of concepts, skills, and strategies. Encouraging learners to explore different facets of society, history, geography, and more, best practices for applying visible learning to social studies curriculum are presented through: ·        A scaffolded approach, including surface-level learning, deep learning, and transfer of learning ·        Examples of strategies, lessons, and activities best suited for each level of learning ·        Planning tools, rubrics, and templates to guide instruction Teachers must understand the impact they have on students and select approaches to maximize that impact. ... Unknown localization key: "more"

Objev podobné jako Visible Learning for Social Studies, Grades K-12 - Julie Stern, John Hattie, Douglas Fisher, Nancy Frey

The most human-friendly book on machine learning Somewhere buried in all the systems that drive artificial intelligence, you'll find machine learning—the process that allows technology to build knowledge based on data and patterns. Machine Learning For Dummies is an excellent starting point for anyone who wants deeper insight into how all this learning actually happens. This book offers an overview of machine learning and its most important practical applications. Then, you'll dive into the tools, code, and math that make machine learning go—and you'll even get step-by-step instructions for testing it out on your own. For an easy-to-follow introduction to building smart algorithms, this Dummies guide is your go-to. Piece together what machine learning is, what it can do, and what it can't doLearn the basics of machine learning code and how it integrates with large datasetsUnderstand the mathematical principles that AI uses to make itself smarterConsider real-world applications of machine learning and write your own algorithms With clear explanations and hands-on instruction, Machine Learning For Dummies is a great entry-level resource for developers looking to get started with AI and machine learning.

Objev podobné jako Machine Learning For Dummies - John Paul Mueller, Luca Massaron

Selected as the Michigan Council of Teachers of Mathematics winter book club book! Rich tasks, collaborative work, number talks, problem-based learning, direct instruction…with so many possible approaches, how do we know which ones work the best? In Visible Learning for Mathematics, six acclaimed educators assert it’s not about which one—it’s about when—and show you how to design high-impact instruction so all students demonstrate more than a year’s worth of mathematics learning for a year spent in school. That’s a high bar, but with the amazing K-12 framework here, you choose the right approach at the right time, depending upon where learners are within three phases of learning: surface, deep, and transfer. This results in "visible" learning because the effect is tangible. The framework is forged out of current research in mathematics combined with John Hattie’s synthesis of more than 15 years of education research involving 300 million students. Chapter by chapter, and equipped with video clips, planning tools, rubrics, and templates, you get the inside track on which instructional strategies to use at each phase of the learning cycle: Surface learning phase: When—through carefully constructed experiences—students explore new concepts and make connections to procedural skills and vocabulary that give shape ... Unknown localization key: "more"

Objev podobné jako Visible Learning for Mathematics, Grades K-12 - Douglas Fisher, Nancy Frey, John Hattie, Sara Delano Moore, Linda M. Gojak, William Mellman

MACHINE LEARNING FOR BUSINESS ANALYTICS Machine learning —also known as data mining or data analytics— is a fundamental part of data science. It is used by organizations in a wide variety of arenas to turn raw data into actionable information. Machine Learning for Business Analytics: Concepts, Techniques, and Applications in R provides a comprehensive introduction and an overview of this methodology. This best-selling textbook covers both statistical and machine learning algorithms for prediction, classification, visualization, dimension reduction, rule mining, recommendations, clustering, text mining, experimentation, and network analytics. Along with hands-on exercises and real-life case studies, it also discusses managerial and ethical issues for responsible use of machine learning techniques. This is the second R edition of Machine Learning for Business Analytics. This edition also includes: A new co-author, Peter Gedeck, who brings over 20 years of experience in machine learning using RAn expanded chapter focused on discussion of deep learning techniquesA new chapter on experimental feedback techniques including A/B testing, uplift modeling, and reinforcement learningA new chapter on responsible data scienceUpdates and new material based on feedback from instructors teaching MBA, Masters in Business Analytics and related programs, undergraduate, diploma and executive courses, and from their studentsA full chapter devoted ... Unknown localization key: "more"

Objev podobné jako Machine Learning for Business Analytics - Peter Gedeck, Galit Shmueli, Peter C. Bruce, Nitin R. Patel, Inbal Yahav

In November 2008, John Hattie’s ground-breaking book Visible Learning synthesised the results of more than fifteen years research involving millions of students and represented the biggest ever collection of evidence-based research into what actually works in schools to improve learning.Visible Learning for Teachers takes the next step and brings those ground breaking concepts to a completely new audience. Written for students, pre-service and in-service teachers, it explains how to apply the principles of Visible Learning to any classroom anywhere in the world. The author offers concise and user-friendly summaries of the most successful interventions and offers practical step-by-step guidance to the successful implementation of visible learning and visible teaching in the classroom.This book:links the biggest ever research project on teaching strategies to practical classroom implementationchampions both teacher and student perspectives and contains step by step guidance including lesson preparation, interpreting learning and feedback during the lesson and post lesson follow upoffers checklists, exercises, case studies and best practice scenarios to assist in raising achievementincludes whole school checklists and advice for school leaders on facilitating visible learning in their institutionnow includes additional meta-analyses bringing the total cited within the research to over 900comprehensively covers numerous areas of learning activity including pupil ... Unknown localization key: "more"

Objev podobné jako Visible Learning for Teachers - John Hattie

MACHINE LEARNING FOR BUSINESS ANALYTICS Machine learning—also known as data mining or predictive analytics—is a fundamental part of data science. It is used by organizations in a wide variety of arenas to turn raw data into actionable information. Machine Learning for Business Analytics: Concepts, Techniques, and Applications with Analytic Solver® Data Mining provides a comprehensive introduction and an overview of this methodology. The fourth edition of this best-selling textbook covers both statistical and machine learning algorithms for prediction, classification, visualization, dimension reduction, rule mining, recommendations, clustering, text mining, experimentation, time series forecasting and network analytics. Along with hands-on exercises and real-life case studies, it also discusses managerial and ethical issues for responsible use of machine learning techniques. This fourth edition of Machine Learning for Business Analytics also includes: An expanded chapter on deep learningA new chapter on experimental feedback techniques, including A/B testing, uplift modeling, and reinforcement learningA new chapter on responsible data scienceUpdates and new material based on feedback from instructors teaching MBA, Masters in Business Analytics and related programs, undergraduate, diploma and executive courses, and from their studentsA full chapter devoted to relevant case studies with more than a dozen cases demonstrating applications for the machine learning techniquesEnd-of-chapter ... Unknown localization key: "more"

Objev podobné jako Machine Learning for Business Analytics - Galit Shmueli, Peter C. Bruce, Nitin R. Patel, Kuber R. Deokar

Humans do a great job of reading text, identifying key ideas, summarizing, making connections, and other tasks that require comprehension and context. Recent advances in deep learning make it possible for computer systems to achieve similar results. Deep Learning for Natural Language Processing teaches you to apply deep learning methods to natural language processing (NLP) to interpret and use text effectively. In this insightful book, (NLP) expert Stephan Raaijmakers distills his extensive knowledge of the latest state-of-the-art developments in this rapidly emerging field. Key features An overview of NLP and deep learning • Models for textual similarity • Deep memory-based NLP • Semantic role labeling • Sequential NLP Audience For those with intermediate Python skills and general knowledge of NLP. No hands-on experience with Keras or deep learning toolkits is required. About the technology Natural language processing is the science of teaching computers to interpret and process human language. Recently, NLP technology has leapfrogged to exciting new levels with the application of deep learning, a form of neural network-based machine learning Stephan Raaijmakers is a senior scientist at TNO and holds a PhD in machine learning and text analytics. He’s the technical coordinator of two large European Union-funded research security-related ... Unknown localization key: "more"

Objev podobné jako Deep Learning for Natural Language Processing - Stephan Raaijmakers

Machine Learning is an integral tool in a business analyst’s arsenal because the rate at which data is being generated from different sources is increasing and working on complex unstructured data is becoming inevitable. Data collection, data cleaning, and data mining are rapidly becoming more difficult to analyze than just importing information from a primary or secondary source. The machine learning model plays a crucial role in predicting the future performance and results of a company. In real-time, data collection and data wrangling are the important steps in deploying the models. Analytics is a tool for visualizing and steering data and statistics. Business analysts can work with different datasets -- choosing an appropriate machine learning model results in accurate analyzing, forecasting the future, and making informed decisions. The global machine learning market was valued at $1.58 billion in 2017 and is expected to reach $20.83 billion in 2024 -- growing at a CAGR of 44.06% between 2017 and 2024. The authors have compiled important knowledge on machine learning real-time applications in business analytics. This book enables readers to get broad knowledge in the field of machine learning models and to carry out their future research work. The future trends of ... Unknown localization key: "more"

Objev podobné jako Machine Learning for Business Analytics

This book covers most of the areas of DRL with a special focus on its mathematical and algorithmic foundations. It is a useful guide for undergraduate and early graduate students to the fast-developing areas of DRL and its myriad applications.

Objev podobné jako An Introduction to Deep Reinforcement Learning - Vinod K. Mishra

Methods by which robots can learn control laws that enable real-time reactivity using dynamical systems; with applications and exercises.This book presents a wealth of machine learning techniques to make the control of robots more flexible and safe when interacting with humans. It introduces a set of control laws that enable reactivity using dynamical systems, a widely used method for solving motion-planning problems in robotics. These control approaches can replan in milliseconds to adapt to new environmental constraints and offer safe and compliant control of forces in contact. The techniques offer theoretical advantages, including convergence to a goal, non-penetration of obstacles, and passivity. The coverage of learning begins with low-level control parameters and progresses to higher-level competencies composed of combinations of skills. Learning for Adaptive and Reactive Robot Control is designed for graduate-level courses in robotics, with chapters that proceed from fundamentals to more advanced content. Techniques covered include learning from demonstration, optimization, and reinforcement learning, and using dynamical systems in learning control laws, trajectory planning, and methods for compliant and force control . Features for teaching in each chapter: applications, which range from arm manipulators to whole-body control of humanoid robots;pencil-and-paper and programming exercises;lecture videos, slides, and MATLAB code examples ... Unknown localization key: "more"

Objev podobné jako Learning for Adaptive and Reactive Robot Control - Aude Billard, Sina Mirrazavi

Quality Learning for Positive Ageing explores the views of older adult learners to understand the factors that contribute to ‘quality’ in later-life learning and how these relate to wellbeing, positive ageing, and gaining protection against cognitive decline.Through capturing and considering the viewpoints of learners, facilitators and learning organisations, the author outlines the specific characteristics of quality that they associate with informal learning and how it can be enhanced through the adoption of simple strategies. Key topics covered include the implications of an increasing ageing population and barriers to older people learning as well as the cognitive, mental wellbeing, health, and social benefits of learning in later life. Illustrated throughout with vignettes of real later-life learners, this thought-provoking text unpicks how learners can maximise the benefits of learning in later life for themselves, how tutors can create learning opportunities that embody the characteristics of quality for them, and how providers can offer an environment that simply allows quality learning to flourish.This accessible and comprehensive text will be of great interest to researchers of gerontology and ageing, educational gerontology, adult education, and lifelong learning as well as those engaged in dementia research.

Objev podobné jako Quality Learning for Positive Ageing - Alan Potter

This book explores the purpose, role and function of the university and examines the disconnection between studentsÂ’ approaches to learning and university strategy. It centres on the idea that it is vital to explore what counts as a university in the twenty-first century, what it is for, and for whom, as well as how it can transcend social divisions. The universities of the twenty-first century need to have larger audiences, a broader voice, a shift away from othering and an effective means of progressing such shifts. What is central to such exploration is the idea that learning needs to be seen as postdigital. With a focus on how the growth of technology has and continues to affect university learning, this book:explores the concepts of the digital and the postdigitalpromotes just and inclusive pedagogies for higher educationconsiders ways to ensure learning is an ethical and political experiencestudies how to understand community and collective values through higher educationsuggests ways of promoting personal and collective responsibility for our world and its peoplespresents ways in which the university can challenge ideologies based on capitalist modes of consumption, privilege and exploitationDigital and Postdigital Learning for Changing Universities is essential reading for anyone seeking to reimagine ... Unknown localization key: "more"

Objev podobné jako Digital and Postdigital Learning for Changing Universities - Savin-Baden Maggi

This social and emotional learning (SEL) workbook for kindergarten students provides daily activities to learn about emotions, actions, relationships, and decision making.180 Days™: Social-Emotional Learning for KindergartenUses daily activities to promote students’ self-awareness, analyze relationships, discover diverse perspectives, and apply what they have learnedBuilds student''s confidence in self-reflection and growth through the use of fiction and nonfiction textsMakes at-home learning, whole class instruction, or small group support, quick and easyConnections will be made to the CASEL competencies, mindfulness, and key affective education initiativesParents appreciate the teacher-approved activity books that keep their child engaged and learning. Great for homeschooling, to reinforce learning at school, and build connections between home and school.Teachers rely on the daily practice workbooks to save them valuable time. The ready to implement activities are perfect to introduce SEL topics for discussion.

Objev podobné jako 180 Daysâ„¢: Social-Emotional Learning for Kindergarten - Jodene Smith, Brenda A. Van Dixhorn

This second edition textbook covers a coherently organized framework for text analytics, which integrates material drawn from the intersecting topics of information retrieval, machine learning, and natural language processing. Particular importance is placed on deep learning methods. The chapters of this book span three broad categories:1. Basic algorithms: Chapters 1 through 7 discuss the classical algorithms for text analytics such as preprocessing, similarity computation, topic modeling, matrix factorization, clustering, classification, regression, and ensemble analysis. 2. Domain-sensitive learning and information retrieval: Chapters 8 and 9 discuss learning models in heterogeneous settings such as a combination of text with multimedia or Web links. The problem of information retrieval and Web search is also discussed in the context of its relationship with ranking and machine learning methods. 3. Natural language processing: Chapters 10 through 16 discuss various sequence-centric and natural language applications, such as feature engineering, neural language models, deep learning, transformers, pre-trained language models, text summarization, information extraction, knowledge graphs, question answering, opinion mining, text segmentation, and event detection. Compared to the first edition, this second edition textbook (which targets mostly advanced level students majoring in computer science and math) has substantially more material on deep learning and natural language processing. Significant ... Unknown localization key: "more"

Objev podobné jako Machine Learning for Text - Charu C. Aggarwal

Machine learning can help managers make better predictions, automate complex tasks and improve business operations. Managers who are familiar with machine learning are better placed to navigate the increasingly digital world we live in. There is a view that machine learning is a highly technical subject that can only be understood by specialists. However, many of the ideas that underpin machine learning are straightforward and accessible to anyone with a bit of curiosity. This book is for managers who want to understand what machine learning is about, but who lack a technical background in computer science, statistics or math. The book describes in plain language what machine learning is and how it works. In addition, it explains how to manage machine learning projects within an organization. This book should appeal to anyone that wants to learn more about using machine learning to drive value in real-world organizations.

Objev podobné jako Machine Learning for Managers - Paul Geertsema

Computer vision-based crack-like object detection has many useful applications, such as inspecting/monitoring pavement surface, underground pipeline, bridge cracks, railway tracks etc. However, in most contexts, cracks appear as thin, irregular long-narrow objects, and often are buried in complex, textured background with high diversity which make the crack detection very challenging. During the past a few years, deep learning technique has achieved great success and has been utilized for solving a variety of object detection problems.This book discusses crack-like object detection problem comprehensively. It starts by discussing traditional image processing approaches for solving this problem, and then introduces deep learning-based methods. It provides a detailed review of object detection problems and focuses on the most challenging problem, crack-like object detection, to dig deep into the deep learning method. It includes examples of real-world problems, which are easy to understand and could be a good tutorial for introducing computer vision and machine learning.

Objev podobné jako Deep Learning for Crack-Like Object Detection - Heng-Da Cheng, Kaige Zhang

A single-volume reference on data science techniques for evaluating and solving business problems using Applied Machine Learning (ML). Applied Machine Learning for Data Science Practitioners offers a practical, step-by-step guide to building end-to-end ML solutions for real-world business challenges, empowering data science practitioners to make informed decisions and select the right techniques for any use case. Unlike many data science books that focus on popular algorithms and coding, this book takes a holistic approach. It equips you with the knowledge to evaluate a range of techniques and algorithms. The book balances theoretical concepts with practical examples to illustrate key concepts, derive insights, and demonstrate applications. In addition to code snippets and reviewing output, the book provides guidance on interpreting results. This book is an essential resource if you are looking to elevate your understanding of ML and your technical capabilities, combining theoretical and practical coding examples. A basic understanding of using data to solve business problems, high school-level math and statistics, and basic Python coding skills are assumed. Written by a recognized data science expert, Applied Machine Learning for Data Science Practitioners covers essential topics, including: Data Science Fundamentals that provide you with an overview of core concepts, laying the ... Unknown localization key: "more"

Objev podobné jako Applied Machine Learning for Data Science Practitioners - Vidya Subramanian

Yves Saint Laurent Loveshine Candy Glow je tónující balzám na rty s 98% přírodních složek. Obsahuje marakujový olej, bambucké a jojobové máslo pro 24hodinovou výživu a pružnost rtů. Balzám okamžitě vyhladí rty, dodá jim přirozený lesk a zvýrazní jejich barvu.

• Obsahuje 98 % ingrediencí přírodního původu (marakujový olej, bambucké a jojobové máslo)
• Poskytuje 24hodinovou výživu a pružnost rtů
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Objev podobné jako Yves Saint Laurent Loveshine Candy Glow tónující balzám na rty 44B Nude Lavalliere 3.1 g

Whether they are new or experienced, teachers are expected to plan and deliver high-quality computing lessons to their pupils. Computing and Digital Learning for Primary Teachers provides an accessible introduction to teaching computing effectively and for deeper understanding in the primary classroom.Filled with practical resources to support lesson design, long-term planning, and assessment, readers will benefit from building their subject knowledge and learning to create engaging lessons for their pupils. Chapters explore:Supporting computational thinking and problem-solving to teach our pupils how to solve problems logically and systematically.Developing pupils’ digital literacy and use of IT, creating exciting opportunities for children’s digital self-expression through film, animation, and 3D design.Managing technology in our schools, such as setting up and maintaining a virtual learning environment (VLE).Cross-curriculum links with STEAM and engineering, allowing children to solve real-world problems by combining their digital literacy with their knowledge of maths, science, and technology.Cost-effective and accessible ways of introducing physical computing and robotics to children.Safe and responsible uses of artificial intelligence (AI) in our primary schools.This essential resource provides a highly practical guide to delivering effective computing lessons in the primary classroom and is a must read for anyone who wishes to become a more confident and knowledgeable ... Unknown localization key: "more"

Objev podobné jako Computing and Digital Learning for Primary Teachers - Owen Dobbing

This textbook is an introductory guide to applied machine learning, specifically for biology students. It familiarizes biology students with the basics of modern computer science and mathematics and emphasizes the real-world applications of these subjects. The chapters give an overview of computer systems and programming languages to establish a basic understanding of the important concepts in computer systems. Readers are introduced to machine learning and artificial intelligence in the field of bioinformatics, connecting these applications to systems biology, biological data analysis and predictions, and healthcare diagnosis and treatment. This book offers a necessary foundation for more advanced computer-based technologies used in biology, employing case studies, real-world issues, and various examples to guide the reader from the basic prerequisites to machine learning and its applications.

Objev podobné jako A Guide to Applied Machine Learning for Biologists

This book explores the benefits of deploying Machine Learning (ML) and Artificial Intelligence (AI) in the health care environment. The authors study different research directions that are working to serve challenges faced in building strong healthcare infrastructure with respect to the pandemic crisis. The authors take note of obstacles faced in the rush to develop and alter technologies during the Covid crisis. They study what can be learned from them and what can be leveraged efficiently. The authors aim to show how healthcare providers can use technology to exploit advances in machine learning and deep learning in their own applications. Topics include remote patient monitoring, data analysis of human behavioral patterns, and machine learning for decision making in real-time.

Objev podobné jako System Design for Epidemics Using Machine Learning and Deep Learning

Foster multilingual learners’ academic success, wellbeing, agency, and belongingThough multilingual learners (MLs) comprise nearly 25% of the school-age population, the most widely-used social emotional learning (SEL) frameworks and programs lack an intentional focus on these students’ unique strengths and challenges. To foster MLs’ academic success and wellbeing, educators must consider students’ cultures, languages, assets, expectations, norms, and life experiences when integrating SEL practices.In this groundbreaking book, Dr. Diane Staehr Fenner and Mindi Teich break down how each of the five competencies in the Collaborative for Academic, Social, and Emotional Learning (CASEL) SEL framework can be implemented with ML success in mind. Staehr Fenner and Teich’s practical and engaging guide provides SEL considerations that are unique to MLs, relevant research, easy-to-implement educator actions, and tools to seamlessly integrate SEL practices into content and language instruction. Additional features include: Tools and practical strategies educators can apply immediately Programmatic and systemic considerations that impact SEL for MLs Examples of successful SEL strategies for MLs currently being used in classrooms Ample opportunities for reflection and application in each chapter Templates to prioritize and integrate SEL for MLs into teaching practicesMLs thrive when they are validated and supported to achieve their goals, empathize with others, ... Unknown localization key: "more"

Objev podobné jako Social Emotional Learning for Multilingual Learners - Diane Staehr Fenner, Mindi Teich

As data continues to grow exponentially, knowledge of data science and machine learning has become more crucial than ever. Machine learning has grown exponentially; however, the abundance of resources can be overwhelming, making it challenging for new learners. This book aims to address this disparity and cater to learners from various non-technical fields, enabling them to utilize machine learning effectively.Adopting a hands-on approach, readers are guided through practical implementations using real datasets and SAS Enterprise Miner, a user-friendly data mining software that requires no programming. Throughout the chapters, two large datasets are used consistently, allowing readers to practice all stages of the data mining process within a cohesive project framework. This book also provides specific guidelines and examples on presenting data mining results and reports, enhancing effective communication with stakeholders.Designed as a guiding companion for both beginners and experienced practitioners, this book targets a wide audience, including students, lecturers, researchers, and industry professionals from various backgrounds.

Objev podobné jako Data Science and Machine Learning for Non-Programmers - Dothang Truong

Adopt a strengths-based, justice-centered approach to teaching multilingualsOffering educators a path to pedagogical justice for multilingual learners, Overhauling Learning for Multilingual Students outlines a comprehensive alternative model for instruction and assessment. With an emphasis on engaging multilingual learners in authentic communication and promoting student agency and creativity, this book is an urgent call-to-action for educators at all levels to value and leverage the many assets that multilingual students bring to every classroom.The book outlines six dimensions of pedagogical justice and offers practical strategies to implement a learner-centered approach that will help all students thrive. Additional features include: An assets-based framework designed to help multilingual learners learn and grow Guidance for shifting instructional strategies away from remediation and test preparation toward an engaging, justice-centered approach Activities to to help students collaboratively build up unique and important ideas (claims and concepts) across disciplinesWritten by scholar, practitioner, and best-selling author, Jeff Zwiers, Overhauling Learning for Multilingual Students supports educators to de-think and rethink traditional one-size-fits-all approaches to teaching and assessing multilingual learners.

Objev podobné jako Overhauling Learning for Multilingual Students - Jeff Zwiers

Exam Board: CCEALevel: GCSESubject: Learning for LifeFirst Teaching: September 2017First Exam: June 2019Enable students to critically engage with the new content and assessment requirements with this fully updated edition of the market-leading Student''s Book for CCEA GCSE Learning for Life and Work- Provides complete coverage of the new content and assessment requirements with support at every stage from experienced teachers and subject experts David McVeigh, Michaella McAllister and Amanda McAleer- Prepares students for assessment with skills-building activities, practice questions and structured guidance on how to approach questions successfully- Helps engage students through accessible diagrams, research activities and a bank of up-to-date case study material- Develops subject knowledge through clear and detailed coverage of the key content structured around the specification

Objev podobné jako CCEA GCSE Learning for Life and Work Second Edition - Amanda McAleer, Michaella McAllister, Joanne McDonnell

Introduction to Stochastic Finance with Market Examples, Second Edition presents an introduction to pricing and hedging in discrete and continuous-time financial models, emphasizing both analytical and probabilistic methods. It demonstrates both the power and limitations of mathematical models in finance, covering the basics of stochastic calculus for finance, and details the techniques required to model the time evolution of risky assets. The book discusses a wide range of classical topics including Black–Scholes pricing, American options, derivatives, term structure modeling, and change of numéraire. It also builds up to special topics, such as exotic options, stochastic volatility, and jump processes.New to this EditionNew chapters on Barrier Options, Lookback Options, Asian Options, Optimal Stopping Theorem, and Stochastic VolatilityContains over 235 exercises and 16 problems with complete solutions available online from the instructor resourcesAdded over 150 graphs and figures, for more than 250 in total, to optimize presentation57 R coding examples now integrated into the book for implementation of the methodsSubstantially class-tested, so ideal for course use or self-studyWith abundant exercises, problems with complete solutions, graphs and figures, and R coding examples, the book is primarily aimed at advanced undergraduate and graduate students in applied mathematics, financial engineering, and economics. It could be ... Unknown localization key: "more"

Objev podobné jako Introduction to Stochastic Finance with Market Examples - Nicolas Privault

Povlečení Nordic Yves modré je vyrobeno z husté bavlny s rostlinným motivem v modrých, béžových a oranžových odstínech. Obsahuje povlak na přikrývku 140 x 200 cm a povlak na polštář 70 x 90 cm, oba s praktickým zipovým uzávěrem. Před prvním použitím se doporučuje vyprat a dodržovat pokyny pro údržbu.

• Vyrobeno z kvalitní husté bavlněné tkaniny v ČR
• Snadné převlékání díky všitému zipu s peckovým jezdcem
• Decentní rostlinný motiv v modrých odstínech se skandinávským vzhledem
• Rozměry udávané po vysrážení s rozměrovou rezervou

Objev podobné jako Kvalitex Bavlněné povlečení Nordic Yves modrá, 140 x 200 cm, 70 x 90 cm

Machine Learning for Kids introduces young readers to the concept of Artificial Intelligence (AI) and the related applications of Machine Learning. Readers learn how to create intelligent games like a rock-paper-scissors game that can learn hand motions and use them to compete against another player; a post sorting game that will recognise the postal code on an envelope and use it to send a letter to the right place. Each project demonstrates a different way that AI is used in the real-world, and readers will be introduced to the biggest issues and challenges that the adoption of AI brings to society.

Objev podobné jako Machine Learning for Kids - Dale Lane

Exam board: CCEALevel: GCSESubject: CitizenshipFirst teaching: September 2017First exams: Summer 2019Target success in CCEA GCSE Learning for Life and Work with this proven formula for effective, structured revision; key content coverage is combined with exam-style tasks and practical tips to create a revision guide that students can rely on to review, strengthen and test their knowledge.With My Revision Notes, every student can:- Plan and manage a successful revision programme using the topic-by-topic planner- Consolidate subject knowledge by working through clear and focused content coverage- Test understanding and identify areas for improvement with regular ''Now Test Yourself'' tasks and answers- Improve exam technique through practice questions and expert tips- Get exam ready with answers to the practice questions available online

Objev podobné jako My Revision Notes: CCEA GCSE Learning for Life and Work: Second Edition - Joanne McDonnell

This book will help you to prepare for and excel in your nursing associate practice placements. Covering all settings and all fields of nursing, the book will show you how to make the most of each placement and transfer learning and skills from one area of practice to another. Key features:Â Â Â Â Â - Fully mapped to the NMC Standards of Proficiency for Nursing Associates (2018) - Helps you prepare for placements in a way that best supports your professional development and personal wellbeing - Case studies and activities introduce you to different settings across all fields of nursing - Focussed specifically on the requirements of the nursing associate role, helping you to develop into a confident professional practitioner THE SERIES: The Understanding Nursing Associate Practice series (UNAP) is a new collection of books uniquely designed to support trainee nursing associates throughout their training and into a professional career.

Objev podobné jako Practice-Based Learning for Nursing Associates

This textbook introduces readers to the theoretical aspects of machine learning (ML) algorithms, starting from simple neuron basics, through complex neural networks, including generative adversarial neural networks and graph convolution networks. Most importantly, this book helps readers to understand the concepts of ML algorithms and enables them to develop the skills necessary to choose an apt ML algorithm for a problem they wish to solve. In addition, this book includes numerous case studies, ranging from simple time-series forecasting to object recognition and recommender systems using massive databases. Lastly, this book also provides practical implementation examples and assignments for the readers to practice and improve their programming capabilities for the ML applications.

Objev podobné jako Machine Learning for Computer Scientists and Data Analysts - Houman Homayoun, Zhiqian Chen, Setareh Rafatirad, Sai Manoj Pudukotai Dinakarrao

Written by more than sixty experts in the area, this book reviews cutting-edge practices in machine learning for financial markets, and explores connections with data science and more traditional approaches. This is an invaluable resource for researchers and graduate students in financial engineering, as well as practitioners in the sector.

Objev podobné jako Machine Learning and Data Sciences for Financial Markets

With this hands-on guide, applied data scientists, machine learning engineers, and practitioners will learn how to build an E2E graph learning pipeline. You'll explore core challenges at each pipeline stage, from data acquisition and representation to real-time inference and feedback loop retraining.

Objev podobné jako Scaling Graph Learning for the Enterprise - Ahmed Menshawy, Sameh Mohamed, Maraim Rizk Masoud

Engage the World Change the World Deep Learning has claimed the attention of educators and policymakers around the world. This book not only defines what deep learning is, but takes up the question of how to mobilize complex, whole-system change and transform learning for all students. Deep Learning is a global partnership that works to: transform the role of teachers to that of activators who design experiences that build global competencies using real-life problem solving; and supports schools, districts, and systems to shift practice and how to measure learning in authentic ways. This comprehensive strategy incorporates practical tools and processes to engage students, educators, and families in new partnerships and drive deep learning. Inside you’ll find: The Deep Learning Framework Vignettes and case studies from K-12 classrooms in 1,200 schools in seven countries Guidance for reaching disadvantaged and differently abled students Sample protocols and rubrics for assessment Videos demonstrating deep learning design and innovative leadership in practice Through learning partnerships, learning environments, new pedagogical practices, and leveraged digital skills, deep learning reaches students as never before — preparing them to be active, engaged participants in their future.

Objev podobné jako Deep Learning - Joanne Quinn, Michael Fullan, Joanne J. McEachen

This step-by-step guide teaches you how to build practical deep learning applications for the cloud and mobile using a hands-on approach.

Objev podobné jako Practical Deep Learning for Cloud and Mobile - Anirudh Koul, Siddha Ganju, Meher Kasam

Cognitive computing simulates human thought processes with self-learning algorithms that utilize data mining, pattern recognition, and natural language processing. The integration of deep learning improves the performance of Cognitive computing systems in many applications, helping in utilizing heterogeneous data sets and generating meaningful insights.

Objev podobné jako Deep Learning for Cognitive Computing Systems

An advanced book for researchers and graduate students working in machine learning and statistics who want to learn about deep learning, Bayesian inference, generative models, and decision making under uncertainty.An advanced counterpart to Probabilistic Machine Learning: An Introduction, this high-level textbook provides researchers and graduate students detailed coverage of cutting-edge topics in machine learning, including deep generative modeling, graphical models, Bayesian inference, reinforcement learning, and causality. This volume puts deep learning into a larger statistical context and unifies approaches based on deep learning with ones based on probabilistic modeling and inference. With contributions from top scientists and domain experts from places such as Google, DeepMind, Amazon, Purdue University, NYU, and the University of Washington, this rigorous book is essential to understanding the vital issues in machine learning.Covers generation of high dimensional outputs, such as images, text, and graphs Discusses methods for discovering insights about data, based on latent variable models Considers training and testing under different distributionsExplores how to use probabilistic models and inference for causal inference and decision makingFeatures online Python code accompanimentÂ

Objev podobné jako Probabilistic Machine Learning - Kevin P. Murphy

The Science of Deep Learning emerged from courses taught by the author that have provided thousands of students with training and experience for their academic studies, and prepared them for careers in deep learning, machine learning, and artificial intelligence in top companies in industry and academia. The book begins by covering the foundations of deep learning, followed by key deep learning architectures. Subsequent parts on generative models and reinforcement learning may be used as part of a deep learning course or as part of a course on each topic. The book includes state-of-the-art topics such as Transformers, graph neural networks, variational autoencoders, and deep reinforcement learning, with a broad range of applications. The appendices provide equations for computing gradients in backpropagation and optimization, and best practices in scientific writing and reviewing. The text presents an up-to-date guide to the field built upon clear visualizations using a unified notation and equations, lowering the barrier to entry for the reader. The accompanying website provides complementary code and hundreds of exercises with solutions.

Objev podobné jako The Science of Deep Learning - Iddo Drori

What is learning? How does it take place? What happens when it goes wrong? The topic of learning has been central to the development of the science of psychology since its inception. Without learning there can be no memory, no language and no intelligence. Indeed it is rather difficult to imagine a part of psychology, or neuroscience, that learning does not touch upon. In this Very Short Introduction Mark Haselgrove describes learning from the perspective of associative theories of classical and instrumental conditioning, and considers why these are the dominant, and best described analyses of learning in contemporary psychology. Tracing the origins of these theories, he discusses the techniques used to study learning in both animals and humans, and considers the importance of learning for animal behaviour and survival.ABOUT THE SERIES: The Very Short Introductions series from Oxford University Press contains hundreds of titles in almost every subject area. These pocket-sized books are the perfect way to get ahead in a new subject quickly. Our expert authors combine facts, analysis, perspective, new ideas, and enthusiasm to make interesting and challenging topics highly readable.

Objev podobné jako Learning - Mark Haselgrove

With an evolutionary advancement of Machine Learning (ML) algorithms, a rapid increase of data volumes and a significant improvement of computation powers, machine learning becomes hot in different applications. However, because of the nature of "black-box" in ML methods, ML still needs to be interpreted to link human and machine learning for transparency and user acceptance of delivered solutions. This edited book addresses such links from the perspectives of visualisation, explanation, trustworthiness and transparency. The book establishes the link between human and machine learning by exploring transparency in machine learning, visual explanation of ML processes, algorithmic explanation of ML models, human cognitive responses in ML-based decision making, human evaluation of machine learning and domain knowledge in transparent ML applications.This is the first book of its kind to systematically understand the current active research activities and outcomes related to human and machine learning. The book will not only inspire researchers to passionately develop new algorithms incorporating human for human-centred ML algorithms, resulting in the overall advancement of ML, but also help ML practitioners proactively use ML outputs for informative and trustworthy decision making.This book is intended for researchers and practitioners involved with machine learning and its applications. The book will especially ... Unknown localization key: "more"

Objev podobné jako Human and Machine Learning

This is a practical guide to the use of technology enhanced learning (TEL) in the classroom. Introducing 50 ways to use technology for learning. Areas covered include:- Gamified learning- Social media- Video streaming- The flipped classroom - Instant feedback tools- And many more.  Guidance on how to use these technologies for learning is complemented by an exploration of their impact on learning. For each example, the opportunities for evidencing progress are evaluated.

Objev podobné jako 50 Ways to Use Technology Enhanced Learning in the Classroom - Peter Atherton