Fun With Machine Learning
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Fun With Machine Learning
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Author : Arockia Liborious
language : en
Publisher: BPB Publications
Release Date : 2023-03-23
Fun With Machine Learning written by Arockia Liborious and has been published by BPB Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-03-23 with Computers categories.
Learn how to use AutoML to leverage Machine Learning for solving business problems KEY FEATURES ● Get familiar with the common machine learning problems and understand how to solve them. ● Understand the importance of different types of data and how to work with them effectively. ● Learn how to use machine learning and AutoML tools to solve real-world problems. DESCRIPTION “Fun with Machine Learning” is an essential guide for anyone looking to learn about machine learning and how it can be used to make informed business decisions. The book covers the basics of machine learning, providing an overview of key concepts and terminology. To fully understand machine learning, it is important to have a basic understanding of statistics and mathematics. The book provides a simple introduction to these topics, making it easy for you to understand the core concepts. One of the key features of the book is its focus on AutoML tools. It introduces you to different AutoML tools and explains how to use them to simplify the data science processes. The book also shows how machine learning can be used to solve real-world business problems, such as predicting customer churn, detecting fraud, and optimizing marketing campaigns. By the end of the book, you will be able to transform raw data into actionable insights with machine learning. WHAT YOU WILL LEARN ● Get a clear understanding of what machine learning is and how it works. ● Learn how to perform regression analysis using Orange. ● Understand how to implement classification In machine learning. ● Get to know more about the clustering and association algorithms. ● Analyze, visualize, manipulate, and forecast time series data with Orange. WHO THIS BOOK IS FOR This book is for Machine Learning engineers, Machine Learning enthusiasts, Data Scientists, beginners, and students who are looking to implement machine learning techniques to solve real-life business problems. It is also a great resource for business leaders who are responsible for making data-driven decisions. TABLE OF CONTENTS 1. Significance of Machine Learning in Today’s Business 2. Know Your Data 3. Up and Running With Analytical Tools 4. Machine Learning in a Nutshell 5. Regression Analysis 6. Classification 7. Clustering and Association 8. Time Series Forecasting 9. Image Analysis 10. Tips and Tricks
Ai Crash Course
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Author : Hadelin de Ponteves
language : en
Publisher:
Release Date : 2019-11-28
Ai Crash Course written by Hadelin de Ponteves and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-28 with Computers categories.
This friendly and accessible guide to AI theory and programming in Python requires no maths or data science background. Key Features Roll up your sleeves and start programming AI models No math, data science, or machine learning background required Packed with hands-on examples, illustrations, and clear step-by-step instructions 5 hands-on working projects put ideas into action and show step-by-step how to build intelligent software Book Description AI is changing the world - and with this book, anyone can start building intelligent software! Through his best-selling video courses, Hadelin de Ponteves has taught hundreds of thousands of people to write AI software. Now, for the first time, his hands-on, energetic approach is available as a book. Taking a graduated approach that starts with the basics before easing readers into more complicated formulas and notation, Hadelin helps you understand what you really need to build AI systems with reinforcement learning and deep learning. Five full working projects put the ideas into action, showing step-by-step how to build intelligent software using the best and easiest tools for AI programming: Google Colab Python TensorFlow Keras PyTorch AI Crash Course teaches everyone to build an AI to work in their applications. Once you've read this book, you're only limited by your imagination. What you will learn Master the key skills of deep learning, reinforcement learning, and deep reinforcement learning Understand Q-learning and deep Q-learning Learn from friendly, plain English explanations and practical activities Build fun projects, including a virtual-self-driving car Use AI to solve real-world business problems and win classic video games Build an intelligent, virtual robot warehouse worker Who this book is for If you want to add AI to your skillset, this book is for you. It doesn't require data science or machine learning knowledge. Just maths basics (high school level).
Machine Learning How Artificial Intelligence Learns Fun Picture Book For K 2 Ai Me Series Big Idea 3
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Author : ReadyAI
language : en
Publisher: Ready AI LLC
Release Date : 2020-10-19
Machine Learning How Artificial Intelligence Learns Fun Picture Book For K 2 Ai Me Series Big Idea 3 written by ReadyAI and has been published by Ready AI LLC this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-10-19 with Computers categories.
Is your child interested in sci-fi, robots, or video games? Is your kid fascinated by smart home assistants and the prospect of self-driving cars? Time to turn that enthusiasm into action and engage with the exciting world of artificial intelligence! AI+Me is a series designed to introduce the 5 Big Ideas of Artificial Intelligence to young learners. Students take a deep dive into the Five Big Ideas of AI (Perception, Representation and Reasoning, Learning, Natural Interaction, and Societal Impact). This is the 3rd book in the AI+Me series focused on Learning. The series is recommended for K-2 students. Why should children be educated about AI? Learning AI opens up a world of opportunities. As the fastest growing area of computer science, AI will become the most important change force when our children grow up so it is critical they learn about it early. AI is fun! The field of AI started with scientists making computers learn to play games. AI is an incredibly fun way to introduce kids to programming and pique their interest in advanced topics like deep learning. Lastly, a topic like AI naturally opens up discussions about our humanity. In our curriculum, we dig deep into questions like “does AI positively or negatively impact society?” In doing so we aim to develop critical thinking skills and encourage students to reflect deeply. Benefits of AI education: - Gets children interested in #STEM education - Improves their problem-solving and critical-thinking skills - Builds their understanding of the tech tools that’ll shape their future - Starts important conversations about the future of humanity What are educators saying: “I really love these books. I think they are absolutely beautiful and very visually engaging ways for students to learn about artificial intelligence. I like how they progress through the topic and terms related to artificial intelligence and help students to attach meaning to what they are learning by the different examples and step-by-step ways that students build their understanding through the book.” - Rachelle Dene Poth, Author of In Other Words, Unconventional, The Future is Now, and Chart a New Course. What are parents saying: “My 1st grader loves this book. She already is really interested in computers, but this book got her thinking about how we actually tell emotions. She started using her camera on her computer to record different expressions.” “My son learned ReadyAI courses before. I let his friend read AI+Me big idea 1. Surprisingly, both of them finished reading the book, with a lot of interest! I Will recommend this book for elementary school students.” “I have been looking for fun ways to introduce AI to my kid, and this definitely nailed it.”
Machine Learning For Education
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Author : Dr. Amit Dua
language : en
Publisher: BPB Publications
Release Date : 2023-05-11
Machine Learning For Education written by Dr. Amit Dua and has been published by BPB Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-05-11 with Computers categories.
A guide to understand the basics of machine learning and its application in the field of education KEY FEATURES ● Create a more efficient and effective learning environment that meets the needs of all students. ● Learn how to use the profound Machine learning advancements in the field of education. ● Understand how students can use machine learning tools to improve their learning and track their progress. DESCRIPTION "Machine Learning for Education" is a book that explores the application of machine learning techniques in the field of education. It covers a wide range of topics, including personalizing learning using machine learning, improving student outcomes, and optimizing educational resources. The book delves into various machine learning techniques such as supervised and unsupervised learning, deep learning, and reinforcement learning, and how they can be applied to different areas of education such as curriculum design, assessment, and student engagement. The book takes a novel approach to explain the applications of machine learning in education through relatable real-life examples, existing problems and proposing thought-provoking solutions to the same. At the end of each chapter, there are crossword puzzles, word grids, and comprehensive exercises designed to reinforce the concepts discussed in the chapter and ensure a thorough understanding. After reading the book, you will have gained the ability to implement the various features and solutions offered by machine learning within the field of education. WHAT YOU WILL LEARN ● Get familiar with the fundamentals of Machine Learning. ● Explore different Machine learning solutions for primary and secondary education. ● Discover ways to use Machine learning enhanced teaching and learning. ● Understand how AI can be used to assess your child's academic progress. ● Understand how Machine learning can assist educational administrators. WHO THIS BOOK IS FOR The book is suitable for anyone who is directly or indirectly involved in the current education landscape, including students, parents, teachers, and educational administrators. No previous knowledge of machine learning is required. TABLE OF CONTENTS 1. Basics of Machine Learning 2. Machine Learning for Students 3. Machine Learning for Parents 4. Machine Learning for Teachers 5. Machine Learning for Educational Administrators
Fundamentals Of Machine Learning For Predictive Data Analytics Second Edition
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Author : John D. Kelleher
language : en
Publisher: MIT Press
Release Date : 2020-10-20
Fundamentals Of Machine Learning For Predictive Data Analytics Second Edition written by John D. Kelleher and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-10-20 with Computers categories.
The second edition of a comprehensive introduction to machine learning approaches used in predictive data analytics, covering both theory and practice. Machine learning is often used to build predictive models by extracting patterns from large datasets. These models are used in predictive data analytics applications including price prediction, risk assessment, predicting customer behavior, and document classification. This introductory textbook offers a detailed and focused treatment of the most important machine learning approaches used in predictive data analytics, covering both theoretical concepts and practical applications. Technical and mathematical material is augmented with explanatory worked examples, and case studies illustrate the application of these models in the broader business context. This second edition covers recent developments in machine learning, especially in a new chapter on deep learning, and two new chapters that go beyond predictive analytics to cover unsupervised learning and reinforcement learning.
Ai Crash Course
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Author : Hadelin de Ponteves
language : en
Publisher: Packt Publishing Ltd
Release Date : 2019-11-29
Ai Crash Course written by Hadelin de Ponteves and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-29 with Computers categories.
Unlock the power of artificial intelligence with top Udemy AI instructor Hadelin de Ponteves. Key FeaturesLearn from friendly, plain English explanations and practical activitiesPut ideas into action with 5 hands-on projects that show step-by-step how to build intelligent softwareUse AI to win classic video games and construct a virtual self-driving carBook Description Welcome to the Robot World ... and start building intelligent software now! Through his best-selling video courses, Hadelin de Ponteves has taught hundreds of thousands of people to write AI software. Now, for the first time, his hands-on, energetic approach is available as a book. Starting with the basics before easing you into more complicated formulas and notation, AI Crash Course gives you everything you need to build AI systems with reinforcement learning and deep learning. Five full working projects put the ideas into action, showing step-by-step how to build intelligent software using the best and easiest tools for AI programming, including Python, TensorFlow, Keras, and PyTorch. AI Crash Course teaches everyone to build an AI to work in their applications. Once you've read this book, you're only limited by your imagination. What you will learnMaster the basics of AI without any previous experienceBuild fun projects, including a virtual-self-driving car and a robot warehouse workerUse AI to solve real-world business problemsLearn how to code in PythonDiscover the 5 principles of reinforcement learningCreate your own AI toolkitWho this book is for If you want to add AI to your skillset, this book is for you. It doesn't require data science or machine learning knowledge. Just maths basics (high school level).
Mastering Net Machine Learning
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Author : Jamie Dixon
language : en
Publisher: Packt Publishing Ltd
Release Date : 2016-03-29
Mastering Net Machine Learning written by Jamie Dixon and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-03-29 with Computers categories.
Master the art of machine learning with .NET and gain insight into real-world applications About This Book Based on .NET framework 4.6.1, includes examples on ASP.NET Core 1.0 Set up your business application to start using machine learning techniques Familiarize the user with some of the more common .NET libraries for machine learning Implement several common machine learning techniques Evaluate, optimize and adjust machine learning models Who This Book Is For This book is targeted at .Net developers who want to build complex machine learning systems. Some basic understanding of data science is required. What You Will Learn Write your own machine learning applications and experiments using the latest .NET framework, including .NET Core 1.0 Set up your business application to start using machine learning. Accurately predict the future using regressions. Discover hidden patterns using decision trees. Acquire, prepare, and combine datasets to drive insights. Optimize business throughput using Bayes Classifier. Discover (more) hidden patterns using KNN and Naive Bayes. Discover (even more) hidden patterns using K-Means and PCA. Use Neural Networks to improve business decision making while using the latest ASP.NET technologies. Explore “Big Data”, distributed computing, and how to deploy machine learning models to IoT devices – making machines self-learning and adapting Along the way, learn about Open Data, Bing maps, and MBrace In Detail .Net is one of the widely used platforms for developing applications. With the meteoric rise of Machine learning, developers are now keen on finding out how can they make their .Net applications smarter. Also, .NET developers are interested into moving into the world of devices and how to apply machine learning techniques to, well, machines. This book is packed with real-world examples to easily use machine learning techniques in your business applications. You will begin with introduction to F# and prepare yourselves for machine learning using .NET framework. You will be writing a simple linear regression model using an example which predicts sales of a product. Forming a base with the regression model, you will start using machine learning libraries available in .NET framework such as Math.NET, Numl.NET and Accord.NET with the help of a sample application. You will then move on to writing multiple linear regressions and logistic regressions. You will learn what is open data and the awesomeness of type providers. Next, you are going to address some of the issues that we have been glossing over so far and take a deep dive into obtaining, cleaning, and organizing our data. You will compare the utility of building a KNN and Naive Bayes model to achieve best possible results. Implementation of Kmeans and PCA using Accord.NET and Numl.NET libraries is covered with the help of an example application. We will then look at many of issues confronting creating real-world machine learning models like overfitting and how to combat them using confusion matrixes, scaling, normalization, and feature selection. You will now enter into the world of Neural Networks and move your line of business application to a hybrid scientific application. After you have covered all the above machine learning models, you will see how to deal with very large datasets using MBrace and how to deploy machine learning models to Internet of Thing (IoT) devices so that the machine can learn and adapt on the fly Style and approach This book will guide you in learning everything about how to tackle the flood of data being encountered these days in your .NET applications with the help of popular machine learning libraries offered by the .NET framework.
Fun Q
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Author : Nick Psaris
language : en
Publisher:
Release Date : 2020-07-16
Fun Q written by Nick Psaris and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-07-16 with categories.
Machine Learning For Kids
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Author : Dale Lane
language : en
Publisher: No Starch Press
Release Date : 2021-01-19
Machine Learning For Kids written by Dale Lane and has been published by No Starch Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-01-19 with Computers categories.
A hands-on, application-based introduction to machine learning and artificial intelligence (AI) that guides young readers through creating compelling AI-powered games and applications using the Scratch programming language. Machine learning (also known as ML) is one of the building blocks of AI, or artificial intelligence. AI is based on the idea that computers can learn on their own, with your help. Machine Learning for Kids will introduce you to machine learning, painlessly. With this book and its free, Scratch-based, award-winning companion website, you'll see how easy it is to add machine learning to your own projects. You don't even need to know how to code! As you work through the book you'll discover how machine learning systems can be taught to recognize text, images, numbers, and sounds, and how to train your models to improve their accuracy. You'll turn your models into fun computer games and apps, and see what happens when they get confused by bad data. You'll build 13 projects step-by-step from the ground up, including: • Rock, Paper, Scissors game that recognizes your hand shapes • An app that recommends movies based on other movies that you like • A computer character that reacts to insults and compliments • An interactive virtual assistant (like Siri or Alexa) that obeys commands • An AI version of Pac-Man, with a smart character that knows how to avoid ghosts NOTE: This book includes a Scratch tutorial for beginners, and step-by-step instructions for every project. Ages 12+
Cbse Artificial Intelligence Class 7
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Author : Manish Soni
language : en
Publisher: Lightup Technologies
Release Date : 2024-11-10
Cbse Artificial Intelligence Class 7 written by Manish Soni and has been published by Lightup Technologies this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-10 with Computers categories.
As we move deeper into the 21st century, the role of technology in our lives continues to expand at an unprecedented pace. Among the most transformative technologies of our time is Artificial Intelligence (AI), which is increasingly becoming a cornerstone of innovation in virtually every field. From healthcare and education to entertainment and transportation, AI shapes how we live, work, and interact with the world around us. For today’s students, understanding AI is not just an option—it’s a necessity. This textbook, meticulously crafted for Class 7 students under the CBSE curriculum, is an essential guide to navigating the fascinating and rapidly evolving world of Artificial Intelligence. The primary goal of this book is to understand AI, making it accessible and engaging for young learners. With its technical jargon and complex algorithms, AI can often seem intimidating. However, through this textbook, we have endeavoured to present AI in a clear, relatable, and intriguing. Each chapter is carefully designed to introduce fundamental concepts and principles of AI, ensuring that students not only understand the theoretical aspects but also see the practical relevance of AI in their everyday lives. Whether it’s exploring how AI helps power their favourite apps, understanding how it assists doctors in diagnosing diseases, or learning how it’s used to improve transportation systems, students will see first-hand how AI is woven into the fabric of modern society. We have incorporated various interactive elements throughout the book to make the learning experience more engaging and effective. These include hands-on activities, project-based learning opportunities, and thought-provoking exercises that encourage students to apply what they’ve learned creatively and innovatively. By working through these activities, students will deepen their understanding of AI and develop critical thinking, problem-solving, and analytical skills that are vital in the digital age. This textbook is more than just an introduction to AI—it’s a call to action. It invites students to be curious, experiment, ask questions, and explore AI's vast possibilities. By nurturing curiosity and creativity from a young age, we can empower students to become tomorrow's innovators, thinkers, and leaders. The journey into the world of AI is just beginning, and this book is your companion on that journey, guiding you as you discover, learn, and grow. As you embark on this exciting adventure into Artificial Intelligence, we encourage you to approach each chapter with an open mind and a spirit of exploration. Today’s learners are shaping the future, and we are excited to see the incredible things you will achieve as you dive into the world of AI. Remember, the knowledge you gain today is the foundation for the innovations of tomorrow. We sincerely thank educators, parents, and students who have made this journey possible. We hope this textbook will educate and inspire a passion for learning and a commitment to making the world a better place through the power of Artificial Intelligence.