{"product_id":"python-machine-learning-machine-learning-and-deep-learning-with-python-scikit-learn-and-tensorflow-paperback-1","title":"Python Machine Learning: Machine Learning and Deep Learning with Python, scikit-learn and Tensorflow - Paperback","description":"\u003cp\u003eby \u003cb\u003eSamuel Burns\u003c\/b\u003e (Author)\u003c\/p\u003e\u003cp\u003eYou are interested in becoming a machine learning expert but don't know where to start from? Don't worry you don't need a big boring and expensive Textbook. This book is the best guide for you.\u003cb\u003e Get your copy NOW  \u003c\/b\u003e\u003cb\u003eWhy this guide is the best one for Data Scientist? \u003c\/b\u003eHere are the reasons: The author has explored everything about machine learning and deep learning right from the basics. \u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eA simple language has been used.\u003c\/li\u003e\n\u003cli\u003eMany examples have been given, both theoretically and programmatically.\u003c\/li\u003e\n\u003cli\u003eScreenshots showing program outputs have been added.\u003c\/li\u003e\n\u003c\/ul\u003e The book is written chronologically, in a step-by-step manner.\u003cb\u003eBook Objectives: \u003c\/b\u003eThe Aims and Objectives of the Book: \u003cul\u003e\n\u003cli\u003eTo help you understand the basics of machine learning and deep learning.\u003c\/li\u003e\n\u003cli\u003eUnderstand the various categories of machine learning algorithms.\u003c\/li\u003e\n\u003cli\u003eTo help you understand how different machine learning algorithms work.\u003c\/li\u003e\n\u003cli\u003eYou will learn how to implement various machine learning algorithms programmatically in Python.\u003c\/li\u003e\n\u003cli\u003eTo help you learn how to use Scikit-Learn and TensorFlow Libraries in Python.\u003c\/li\u003e\n\u003cli\u003eTo help you know how to analyze data programmatically to extract patterns, trends, and relationships between variables.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cb\u003eWho this Book is for?\u003c\/b\u003eHere are the target readers for this book: \u003cul\u003e\n\u003cli\u003eAnybody who is a complete beginner to machine learning in Python.\u003c\/li\u003e\n\u003cli\u003eAnybody who needs to advance their programming skills in Python for machine learning programming and deep learning.\u003c\/li\u003e\n\u003cli\u003eProfessionals in data science.\u003c\/li\u003e\n\u003cli\u003eProfessors, lecturers or tutors who are looking to find better ways to explain machine learning to their students in the simplest and easiest way.\u003c\/li\u003e\n\u003cli\u003eStudents and academicians, especially those focusing on neural networks, machine learning, and deep learning.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cb\u003eWhat do you need for this Book? \u003c\/b\u003eYou are required to have installed the following on your computer: \u003cul\u003e\n\u003cli\u003ePython 3.X\u003c\/li\u003e\n\u003cli\u003eNumpy\u003c\/li\u003e\n\u003cli\u003ePandas\u003c\/li\u003e\n\u003cli\u003eMatplotlib\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eThe Author guides you on how to install the rest of the Python libraries that are required for machine learning and deep learning.\u003c\/p\u003e\u003cb\u003e What is inside the book: \u003c\/b\u003e\u003cul\u003e\n\u003cli\u003e Getting Started \u003c\/li\u003e\n\u003cli\u003eEnvironment Setup \u003c\/li\u003e\n\u003cli\u003eUsing Scikit-Learn \u003c\/li\u003e\n\u003cli\u003eLinear Regression with Scikit-Learn \u003c\/li\u003e\n\u003cli\u003ek-Nearest Neighbors Algorithm \u003c\/li\u003e\n\u003cli\u003eK-Means Clustering \u003c\/li\u003e\n\u003cli\u003eSupport Vector Machines \u003c\/li\u003e\n\u003cli\u003eNeural Networks with Scikit-learn \u003c\/li\u003e\n\u003cli\u003eRandom Forest Algorithm \u003c\/li\u003e\n\u003cli\u003eUsing TensorFlow \u003c\/li\u003e\n\u003cli\u003eRecurrent Neural Networks with TensorFlow \u003c\/li\u003e\n\u003cli\u003eLinear Classifier \u003c\/li\u003e\n\u003c\/ul\u003eThis book will teach you machine learning classifiers using scikit-learn and tenserflow . The book provides a great overview of functions you can use to build a support vector machine, decision tree, perceptron, and k-nearest neighbors. Thanks of this book you will be able to set up a learning pipeline that handles input and output data, pre-processes it, selects meaningful features, and applies a classifier on it. This book offers a lot of insight into machine learning for both beginners, as well as for professionals, who already use some machine learning techniques. Concepts and the background of these concepts are explained clearly in this tutorial.\u003cdiv\u003e\n\u003cstrong\u003eNumber of Pages:\u003c\/strong\u003e 178\u003c\/div\u003e\u003cdiv\u003e\n\u003cstrong\u003eDimensions:\u003c\/strong\u003e 0.41 x 9 x 6 IN\u003c\/div\u003e\u003cdiv\u003e\n\u003cstrong\u003ePublication Date:\u003c\/strong\u003e March 13, 2019\u003c\/div\u003e","brand":"Books by splitShops","offers":[{"title":"Default Title","offer_id":42721519468607,"sku":"9781090434166","price":24.28,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0105\/8226\/1823\/files\/2c9025591696a3aee79cf5f1374f433e.webp?v=1765092650","url":"https:\/\/dhlswag.com\/products\/python-machine-learning-machine-learning-and-deep-learning-with-python-scikit-learn-and-tensorflow-paperback-1","provider":"BBB","version":"1.0","type":"link"}