{"product_id":"machine-learning-for-dummies-isbn-9781119724018","title":"Machine Learning For Dummies","description":"\u003cb\u003eOne of Mark Cuban’s top reads for better understanding A.I. (inc.com, 2021)\u003c\/b\u003e \u003cp\u003e\u003cb\u003eYour comprehensive entry-level guide to machine learning\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eWhile machine learning expertise doesn’t quite mean you can create your own Turing Test-proof android—as in the movie Ex Machina—it is a form of artificial intelligence and one of the most exciting technological means of identifying opportunities and solving problems fast and on a large scale. Anyone who masters the principles of machine learning is mastering a big part of our tech future and opening up incredible new directions in careers that include fraud detection, optimizing search results, serving real-time ads, credit-scoring, building accurate and sophisticated pricing models—and way, way more.\u003c\/p\u003e \u003cp\u003eUnlike most machine learning books, the fully updated 2nd Edition of Machine \u003ci\u003eLearning For Dummies\u003c\/i\u003e doesn't assume you have years of experience using programming languages such as Python (R source is also included in a downloadable form with comments and explanations), but lets you in on the ground floor, covering the entry-level materials that will get you up and running building models you need to perform practical tasks. It takes a look at the underlying—and fascinating—math principles that power machine learning but also shows that you don't need to be a math whiz to build fun new tools and apply them to your work and study.\u003c\/p\u003e \u003cul\u003e \u003cli\u003eUnderstand the history of AI and machine learning\u003c\/li\u003e \u003cli\u003eWork with Python 3.8 and TensorFlow 2.x (and R as a download)\u003c\/li\u003e \u003cli\u003eBuild and test your own models\u003c\/li\u003e \u003cli\u003eUse the latest datasets, rather than the worn out data found in other books\u003c\/li\u003e \u003cli\u003eApply machine learning to real problems\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003eWhether you want to learn for college or to enhance your business or career performance, this friendly beginner's guide is your best introduction to machine learning, allowing you to become quickly confident using this amazing and fast-developing technology that's impacting lives for the better all over the world.\u003c\/p\u003e \u003cp\u003eIntroduction   1\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart 1: Introducing How Machines Learn 5\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eChapter 1: Getting the Real Story about AI 7\u003c\/p\u003e \u003cp\u003eChapter 2: Learning in the Age of Big Data 23\u003c\/p\u003e \u003cp\u003eChapter 3: Having a Glance at the Future 37\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart 2: Preparing Your Learning Tools   47\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eChapter 4: Installing a Python Distribution 49\u003c\/p\u003e \u003cp\u003eChapter 5: Beyond Basic Coding in Python   67\u003c\/p\u003e \u003cp\u003eChapter 6: Working with Google Colab   87\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart 3: Getting Started with the Math Basics   115\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eChapter 7: Demystifying the Math Behind Machine Learning   117\u003c\/p\u003e \u003cp\u003eChapter 8: Descending the Gradient   139\u003c\/p\u003e \u003cp\u003eChapter 9: Validating Machine Learning   153\u003c\/p\u003e \u003cp\u003eChapter 10: Starting with Simple Learners   175\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart 4: Learning from Smart and Big Data   197\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eChapter 11: Preprocessing Data 199\u003c\/p\u003e \u003cp\u003eChapter 12: Leveraging Similarity 221\u003c\/p\u003e \u003cp\u003eChapter 13: Working with Linear Models the Easy Way   243\u003c\/p\u003e \u003cp\u003eChapter 14: Hitting Complexity with Neural Networks 271\u003c\/p\u003e \u003cp\u003eChapter 15: Going a Step Beyond Using Support Vector Machines 307\u003c\/p\u003e \u003cp\u003eChapter 16: Resorting to Ensembles of Learners   319\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart 5: Applying Learning to Real Problems 339\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eChapter 17: Classifying Images   341\u003c\/p\u003e \u003cp\u003eChapter 18: Scoring Opinions and Sentiments   361\u003c\/p\u003e \u003cp\u003eChapter 19: Recommending Products and Movies 383\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart 6: The Part of Tens   405\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eChapter 20: Ten Ways to Improve Your Machine Learning Models   407\u003c\/p\u003e \u003cp\u003eChapter 21: Ten Guidelines for Ethical Data Usage 415\u003c\/p\u003e \u003cp\u003eChapter 22: Ten Machine Learning Packages to Master   423\u003c\/p\u003e \u003cp\u003eIndex   431\u003c\/p\u003e \u003cp\u003e\u003cb\u003eJohn Mueller\u003c\/b\u003e has produced hundreds of books and articles on topics ranging from networking to home security and from database management to heads-down programming.\u003c\/p\u003e \u003cp\u003e\u003cb\u003eLuca Massaron\u003c\/b\u003e is a senior expert in data science who has been involved with quantitative methods since 2000. He is a Google Developer Expert (GDE) in machine learning.\u003c\/p\u003e \u003cp\u003e\u003cb\u003eFun ways to work and play with new machine learning tools\u003c\/b\u003e \u003c\/p\u003e\u003cp\u003eWhat, exactly, is machine learning? How can you implement it, and which tools will you need? This book shows you how to build predictive models, detect anomalies, analyze text and images, and more. Machine learning makes all this possible. Dive into this exciting new technology with \u003ci\u003eMachine Learning For Dummies,\u003c\/i\u003e 2nd Edition. This even-friendlier new edition answers your questions — guiding you in learning essential programming and concepts from scratch! Here is the entry-level info you need to get up and running with machine learning. \u003c\/p\u003e\u003cp\u003e\u003cb\u003eInside. . .\u003c\/b\u003e \u003c\/p\u003e\u003cli\u003e\u003cbl\u003eIntro to machine learning and AI\u003c\/bl\u003e\u003c\/li\u003e\u003cli\u003e\u003cbl\u003e Big data and algorithms explained\u003c\/bl\u003e\u003c\/li\u003e\u003cli\u003e\u003cbl\u003e Demystifying the math behind AI\u003c\/bl\u003e\u003c\/li\u003e\u003cli\u003e\u003cbl\u003e Many best practice examples\u003c\/bl\u003e\u003c\/li\u003e\u003cli\u003e\u003cbl\u003e Practical uses for machine learning\u003c\/bl\u003e\u003c\/li\u003e\u003cli\u003e\u003cbl\u003e Real-world datasets\u003c\/bl\u003e\u003c\/li\u003e\u003cli\u003e\u003cbl\u003e Ethical approaches to data use\u003c\/bl\u003e\u003c\/li\u003e","brand":"For Dummies","offers":[{"title":"Default Title","offer_id":47989548482789,"sku":"NP9781119724018","price":34.99,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1842\/7735\/files\/9781119724018.jpg?v=1761784552","url":"https:\/\/k12savings.com\/es\/products\/machine-learning-for-dummies-isbn-9781119724018","provider":"K12savings","version":"1.0","type":"link"}