
Product Description Unlock powerful machine learning techniques and solve any machine learning problem you come across with Python Key Features Understand the key frameworks in data science, machine learning, and deep learning Leverage scikit-learn and TensorFlow to fully explore the machine learning ecosystem Apply machine learning and deep learning algorithms to challenging real-world datasets Book Description Machine learning is becoming more and more transformational to businesses every passing day. Machine Learning with TensorFlow and scikit-learn offers you the practical knowledge and techniques you need to create and contribute to machine learning, deep learning, and modern data analysis using the latest cutting-edge tools. You'll begin this Learning Path by working on techniques that you need to create and contribute to the field of machine learning. Coverage of the TensorFlow deep learning library and the scikit-learn code are included, as they are two of the most popular frameworks used in machine learning. This Learning Path is loaded with several examples that show you how to leverage the open source Python libraries to create machine learning models that easily solve your everyday tasks and problems. You'll learn how to use complex Scikit-learn features and the TensorFlow computing library for intensive computation, digging deeper to gain more insights into your data than ever before. You will explore topics right from mathematical operations to implementing various supervised, unsupervised, and deep learning algorithms with scikit-learn. By the end of this Learning Path, you'll be equipped with tools that will help you maximize the potential of machine learning. This Learning Path includes content from the following Packt products: Python Machine Learning, Second Edition by Sebastian Raschka, Vahid Mirjalili TensorFlow Machine Learning Cookbook, Second Edition by Nick McClure Scikit-learn Cookbook, Second Edition by Julian Avila, Trent Hauck What you w
Page Count:
805
Publication Date:
2019-01-09
ISBN-10:
1789956196
ISBN-13:
9781789956191
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