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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 DescriptionMachine 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
This book explores the application of machine learning techniques using Python to unlock growth in contemporary marketplaces. It aims to provide a solid foundation in the machine learning design process, enabling readers to build customized models for unique problems by tackling real-world complexities with innovative techniques. The content begins with Python fundamentals, focusing on powerful libraries like scikit-learn, Theano, and Keras, before progressing into data science and advanced feature engineering.
The book is positioned as a guide for those seeking to enter the field of machine learning, emphasizing practical application through Python. It aims to equip readers with the ability to understand and design effective machine learning systems. The content covers foundational Python libraries and progresses to more advanced data science concepts, suggesting a structured approach for skill development in this rapidly growing area.
Page Count:
901
Publication Date:
2016-08-31
Publisher:
Packt Publishing
ISBN-10:
1787128547
ISBN-13:
9781787128545
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