Python: Deeper Insights into Machine Learning: Leverage benefits of machine learning techniques using Python

Raschka, Sebastian,Julian, David,Hearty, John

ISBN 10: 1787128571 / ISBN 13: 9781787128576

Verlag: Packt Publishing, 2017

Beschreibung

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Bibliografische Details

• Titel: Python: Deeper Insights into Machine Learning: Leverage benefits of machine learning techniques using Python
• Verlag: Packt Publishing
• Veröffentlichungsdatum: 2017
• Sprache: Englisch
• ISBN-10: 1787128571
• ISBN-13: 9781787128576
• Bindung: paperback
• Zustand: Good

Über diesen Titel

Inhaltsangabe

Leverage benefits of machine learning techniques using Python.

Key Features

• Improve and optimise machine learning systems using effective strategies.
• Develop a strategy to deal with a large amount of data.
• Use of Python code for implementing a range of machine learning algorithms and techniques.

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.

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

Who this book is for

This title is for data scientist and researchers who are already into the field of data science and want to see machine learning in action and explore its real-world application. Prior knowledge of Python programming and mathematics is must with basic knowledge of machine learning concepts.

Über die Autorin bzw. den Autor

Sebastian Raschka is an Assistant Professor of Statistics at the University of Wisconsin-Madison focusing on machine learning and deep learning research. Some of his recent research methods have been applied to solving problems in the field of biometrics for imparting privacy to face images. Other research focus areas include the development of methods related to model evaluation in machine learning, deep learning for ordinal targets, and applications of machine learning to computational biology.