{"product_id":"practical-deep-learning-a-python-based-introduction-paperback","title":"Practical Deep Learning: A Python-Based Introduction - Paperback","description":"\u003cp\u003eby \u003cb\u003eRonald T. Kneusel\u003c\/b\u003e (Author)\u003c\/p\u003e\u003cp\u003e\u003cb\u003e\u003ci\u003ePractical Deep Learning\u003c\/i\u003e teaches total beginners how to build the datasets and models needed to train neural networks for your own DL projects.\u003c\/b\u003e \u003c\/p\u003e\u003cp\u003e\u003c\/p\u003eIf you've been curious about machine learning but didn't know where to start, this is the book you've been waiting for. Focusing on the subfield of machine learning known as \u003ci\u003edeep learning\u003c\/i\u003e, it explains core concepts and gives you the foundation you need to start building your own models. Rather than simply outlining recipes for using existing toolkits, \u003ci\u003ePractical Deep Learning\u003c\/i\u003e teaches you the why of deep learning and will inspire you to explore further. \u003cp\u003e\u003c\/p\u003eAll you need is basic familiarity with computer programming and high school math--the book will cover the rest. After an introduction to Python, you'll move through key topics like how to build a good training dataset, work with the scikit-learn and Keras libraries, and evaluate your models' performance. \u003cp\u003e\u003c\/p\u003eYou'll also learn: \u003cbr\u003e\u003cli\u003eHow to use classic machine learning models like k-Nearest Neighbors, Random Forests, and Support Vector Machines\u003c\/li\u003e\u003cli\u003eHow neural networks work and how they're trained\u003c\/li\u003e\u003cli\u003eHow to use convolutional neural networks\u003c\/li\u003e\u003cli\u003eHow to develop a successful deep learning model from scratch\u003c\/li\u003e \u003cbr\u003eYou'll conduct experiments along the way, building to a final case study that incorporates everything you've learned. \u003cp\u003e\u003c\/p\u003eThe perfect introduction to this dynamic, ever-expanding field, \u003ci\u003ePractical Deep Learning\u003c\/i\u003e will give you the skills and confidence to dive into your own machine learning projects.\u003ch3\u003eAuthor Biography\u003c\/h3\u003e\u003cp\u003eRon Kneusel has been working in the machine learning industry since 2003 and has been programming in Python since 2004. He received a PhD in Computer Science from UC Boulder in 2016 and is the author of two previous books: \u003ci\u003eNumbers and Computers\u003c\/i\u003e and \u003ci\u003eRandom Numbers and Computers\u003c\/i\u003e.\u003c\/p\u003e\u003cdiv\u003e\n\u003cstrong\u003eNumber of Pages:\u003c\/strong\u003e 464\u003c\/div\u003e\u003cdiv\u003e\n\u003cstrong\u003eDimensions:\u003c\/strong\u003e 1.3 x 9.2 x 7 IN\u003c\/div\u003e\u003cdiv\u003e\n\u003cstrong\u003ePublication Date:\u003c\/strong\u003e February 23, 2021\u003c\/div\u003e","brand":"Books by splitShops","offers":[{"title":"Default Title","offer_id":42163224641671,"sku":"9781718500747","price":59.99,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0601\/2623\/2711\/files\/96927101dc388ef13b0dc52828c42058.webp?v=1733295719","url":"https:\/\/booksby.splitshops.com\/products\/practical-deep-learning-a-python-based-introduction-paperback","provider":"Books by splitShops","version":"1.0","type":"link"}