Python: Deeper Insights into Machine Learning

Leverage benefits of machine learning techniques using Python

Python: Deeper Insights into Machine Learning

Sebastian Raschka, David Julian, John Hearty

12 customer reviews
Leverage benefits of machine learning techniques using Python
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Book Details

ISBN 139781787128576
Paperback901 pages

Book Description

Machine learning and predictive analytics are becoming one of the key strategies for unlocking growth in a challenging contemporary marketplace. It is one of the fastest growing trends in modern computing, and everyone wants to get into the field of machine learning. In order to obtain sufficient recognition in this field, one must be able to understand and design a machine learning system that serves the needs of a project.

The idea is to prepare a learning path that will help you to tackle the real-world complexities of modern machine learning with innovative and cutting-edge techniques. Also, it will give you a solid foundation in the machine learning design process, and enable you to build customized machine learning models to solve unique problems.

The course begins with getting your Python fundamentals nailed down. It focuses on answering the right questions that cove a wide range of powerful Python libraries, including scikit-learn Theano and Keras.After getting familiar with Python core concepts, it’s time to dive into the field of data science. You will further gain a solid foundation on the machine learning design and also learn to customize models for solving problems.

At a later stage, you will get a grip on more advanced techniques and acquire a broad set of powerful skills in the area of feature selection and feature engineering.

Table of Contents

Chapter 14: Thinking in Machine Learning
Chapter 17: Models – Learning from Information
Chapter 26: Convolutional Neural Networks
Chapter 31: Additional Python Machine Learning Tools
Chapter 32: Chapter Code Requirements

What You Will Learn

  • Learn to write clean and elegant Python code that will optimize the strength of your algorithms
  • Uncover hidden patterns and structures in data with clustering
  • Improve accuracy and consistency of results using powerful feature engineering techniques
  • Gain practical and theoretical understanding of cutting-edge deep learning algorithms
  • Solve unique tasks by building models
  • Get grips on the machine learning design process

Authors

Table of Contents

Chapter 14: Thinking in Machine Learning
Chapter 17: Models – Learning from Information
Chapter 26: Convolutional Neural Networks
Chapter 31: Additional Python Machine Learning Tools
Chapter 32: Chapter Code Requirements

Book Details

ISBN 139781787128576
Paperback901 pages
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