Python Machine Learning By Example : Industry adopted applications with the clear demonstration of Machine Learning concepts using Python libraries, 2/e
暫譯: Python 機器學習實例：行業應用與 Python 函式庫清晰展示機器學習概念，第二版

Grasp machine learning techniques and algorithms with Python, TensorFlow and scikit through real-world examples

Key Features

• Exploit the power of Python to dive deep into the world of data mining and analytics
• Learn machine learning algorithms to solve complex challenges faced by data scientists today
• Use modern Python libraries like Tensorflow and Keras to create smart cognitive actions for your projects

Book Description

A resurging interest in machine learning is due to the same factors that have made data mining and Bayesian analysis more popular than ever. This book is your entry point to machine learning.

This book starts with an introduction to machine learning and the Python language and shows you how to complete the setup. Moving ahead, you will learn all the important concepts such as, exploratory data analysis, data visualization and preprocessing, feature engineering, classification, regression, clustering, natural language processing, and model performance evaluation, as well as large-scale learning. With the help of various projects included, you will find it intriguing to acquire the mechanics of several important machine learning algorithms - they are no more obscure as they thought. Toward the end, you will gather a broad picture of the machine learning ecosystem and best practices of applying machine learning techniques.

Through this book, you will learn to tackle data-driven problems and implement your solutions with the powerful yet simple language, Python, and popular Python packages and tools such as TensorFlow, scikit-learn, NLTK, and Spark. Interesting and easy-to-follow examples, to name some, news topic modeling and classification, spam email detection, online ad click-through prediction, stock prices forecast, will keep you glued till you reach your goal.

What you will learn

• Understand the important concepts in machine learning and data science
• Exploit the power of Python to dive deep into the world of data mining and analytics
• Scale up model training to million and more data points using Apache Hadoop and Spark
• Delve deep into text and natural language processing using Python library such NLTK and Gensim
• Select and build a machine learning model, evaluate its performance and optimize it
• Master the Implementation of popular classification, regression, clustering and feature engineering algorithms both from scratch in Python and using TensorFlow and scikit-learn

Who This Book Is For

This book is for Machine Learning Aspirants, Data Analysts, Data Engineers who are highly passionate about Machine Learning and wants to start getting employed in Machine Learning assignments. Prior knowledge of python coding is assumed and basic familiarity with the statistical concept is beneficial although not a mandate