{"product_id":"libro-grokking-machine-learning","title":"Libro: Grokking Machine Learning","description":"\u003ctable style=\"border-collapse:collapse;margin-bottom:16px;width:100%\"\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003cstrong\u003eFormato\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd\u003eTapa Blanda\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003cstrong\u003eNúmero de páginas\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd\u003e512\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/table\u003e\u003cp\u003eDiscover valuable machine learning techniques you can understand and apply using just high-school math.\u003cbr\u003e\u003cbr\u003eIn Grokking Machine Learning you will learn:\u003cbr\u003e\u003cbr\u003eSupervised algorithms for classifying and splitting data\u003cbr\u003eMethods for cleaning and simplifying data\u003cbr\u003eMachine learning packages and tools\u003cbr\u003eNeural networks and ensemble methods for complex datasets\u003cbr\u003e\u003cbr\u003eGrokking Machine Learning teaches you how to apply ML to your projects using only standard Python code and high school-level math. No specialist knowledge is required to tackle the hands-on exercises using Python and readily available machine learning tools. Packed with easy-to-follow Python-based exercises and mini-projects, this book sets you on the path to becoming a machine learning expert.\u003cbr\u003e\u003cbr\u003ePurchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.\u003cbr\u003e\u003cbr\u003eAbout the technology\u003cbr\u003eDiscover powerful machine learning techniques you can understand and apply using only high school math! Put simply, machine learning is a set of techniques for data analysis based on algorithms that deliver better results as you give them more data. ML powers many cutting-edge technologies, such as recommendation systems, facial recognition software, smart speakers, and even self-driving cars. This unique book introduces the core concepts of machine learning, using relatable examples, engaging exercises, and crisp illustrations.\u003cbr\u003e\u003cbr\u003eAbout the book\u003cbr\u003eGrokking Machine Learning presents machine learning algorithms and techniques in a way that anyone can understand. This book skips the confused academic jargon and offers clear explanations that require only basic algebra. As you go, you’ll build interesting projects with Python, including models for spam detection and image recognition. You’ll also pick up practical skills for cleaning and preparing data.\u003cbr\u003e\u003cbr\u003eWhat's inside\u003cbr\u003e\u003cbr\u003eSupervised algorithms for classifying and splitting data\u003cbr\u003eMethods for cleaning and simplifying data\u003cbr\u003eMachine learning packages and tools\u003cbr\u003eNeural networks and ensemble methods for complex datasets\u003cbr\u003e\u003cbr\u003eAbout the reader\u003cbr\u003eFor readers who know basic Python. No machine learning knowledge necessary.\u003cbr\u003e\u003cbr\u003eAbout the author\u003cbr\u003eLuis G. Serrano is a research scientist in quantum artificial intelligence. Previously, he was a Machine Learning Engineer at Google and Lead Artificial Intelligence Educator at Apple.\u003cbr\u003e\u003cbr\u003eTable of Contents\u003cbr\u003e1 What is machine learning? It is common sense, except done by a computer\u003cbr\u003e2 Types of machine learning\u003cbr\u003e3 Drawing a line close to our points: Linear regression\u003cbr\u003e4 Optimizing the training process: Underfitting, overfitting, testing, and regularization\u003cbr\u003e5 Using lines to split our points: The perceptron algorithm\u003cbr\u003e6 A continuous approach to splitting points: Logistic classifiers\u003cbr\u003e7 How do you measure classification models? Accuracy and its friends\u003cbr\u003e8 Using probability to its maximum: The naive Bayes model\u003cbr\u003e9 Splitting data by asking questions: Decision trees\u003cbr\u003e10 Combining building blocks to gain more power: Neural networks\u003cbr\u003e11 Finding boundaries with style: Support vector machines and the kernel method\u003cbr\u003e12 Combining models to maximize results: Ensemble learning\u003cbr\u003e13 Putting it all in practice: A real-life example of data engineering and machine learning\u003c\/p\u003e","brand":"Manning Publications","offers":[{"title":"Default Title","offer_id":59938881405009,"sku":"1617295914","price":414.0,"currency_code":"PEN","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0669\/6455\/3809\/files\/81bK3MbfvML.jpg?v=1785427411","url":"https:\/\/provetodo.cl\/es-pe\/products\/libro-grokking-machine-learning","provider":"Provetodo ","version":"1.0","type":"link"}