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Building Machine Learning Systems with Python: Expand your Python knowledge and learn all about machine-learning libraries in this user-friendly manual. ML is the next big breakthrough in technol

Building Machine Learning Systems with Python: Expand your Python knowledge and learn all about machine-learning libraries in this user-friendly manual. ML is the next big breakthrough in technol

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Build intelligent end-to-end machine learning systems with Python

Key Features

  • Use scikit-learn and TensorFlow to train your machine learning models
  • Implement popular supervised and unsupervised machine learning algorithms in Python
  • Discover best practices for building production-grade machine learning systems from scratch

Book Description

Machine learning enables systems to make predictions based on historical data. Python is one of the most popular languages used to develop machine learning applications, thanks to its extensive library support. This updated third edition of Building Machine Learning Systems with Python helps you get up to speed with the latest trends in artificial intelligence (AI).

With this guide's hands-on approach, you'll learn to build state-of-the-art machine learning models from scratch. Complete with ready-to-implement code and real-world examples, the book starts by introducing the Python ecosystem for machine learning. You'll then learn best practices for preparing data for analysis and later gain insights into implementing supervised and unsupervised machine learning techniques such as classification, regression and clustering. As you progress, you'll understand how to use Python's scikit-learn and TensorFlow libraries to build production-ready and end-to-end machine learning system models, and then fine-tune them for high performance.

By the end of this book, you'll have the skills you need to confidently train and deploy enterprise-grade machine learning models in Python.

What you will learn

  • Build a classification system that can be applied to text, images, and sound
  • Solve regression-related problems using scikit-learn and TensorFlow
  • Recommend products to users based on their previous purchases
  • Explore different methods of applying deep neural networks to your data
  • Understand recent advances in computer vision and natural language processing (NLP)
  • Deploy Amazon Web Services (AWS) to run data models on the cloud

Who this book is for:

This book is for data scientists, machine learning developers, and Python developers who want to learn how to build increasingly complex machine learning systems. Prior knowledge of Python programming is expected.

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About the Book

Expand your Python knowledge and learn all about machine-learning libraries in this user-friendly manual. ML is the next big breakthrough in technology and this book will give you the head-start you need.


Key Features:

  • Master Machine Learning using a broad set of Python libraries and start building your own Python-based ML systems
  • Covers classification, regression, feature engineering, and much more guided by practical examples
  • A scenario-based tutorial to get into the right mind-set of a machine learner (data exploration) and successfully implement this in your new or existing projects


Book Description:

Machine learning, the field of building systems that learn from data, is exploding on the Web and elsewhere. Python is a wonderful language in which to develop machine learning applications. As a dynamic language, it allows for fast exploration and experimentation and an increasing number of machine learning libraries are developed for Python.Building Machine Learning system with Python shows you exactly how to find patterns through raw data. The book starts by brushing up on your Python ML knowledge and introducing libraries, and then moves on to more serious projects on datasets, Modelling, Recommendations, improving recommendations through examples and sailing through sound and image processing in detail. Using open-source tools and libraries, readers will learn how to apply methods to text, images, and sounds. You will also learn how to evaluate, compare, and choose machine learning techniques. Written for Python programmers, Building Machine Learning Systems with Python teaches you how to use open-source libraries to solve real problems with machine learning. The book is based on real-world examples that the user can build on.


Readers will learn how to write programs that classify the quality of StackOverflow answers or whether a music file is Jazz or Metal. They will learn regression, which is demonstrated on how to recommend movies to users. Advanced topics such as topic modeling (finding a text's most important topics), basket analysis, and cloud computing are covered as well as many other interesting aspects.Building Machine Learning Systems with Python will give you the tools and understanding required to build your own systems, which are tailored to solve your problems.



What You Will Learn:

  • Build a classification system that can be applied to text, images, or sounds
  • Use scikit-learn, a Python open-source library for machine learning
  • Explore the mahotas library for image processing and computer vision
  • Build a topic model of the whole of Wikipedia
  • Get to grips with recommendations using the basket analysis
  • Use the Jug package for data analysis
  • Employ Amazon Web Services to run analyses on the cloud
  • Recommend products to users based on past purchases

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Product Details
  • ISBN-13: 9781782161400
  • Publisher: Packt Publishing
  • Publisher Imprint: Packt Publishing
  • Depth: 13
  • Language: English
  • Returnable: N
  • Sub Title: Expand your Python knowledge and learn all about machine-learning libraries in this user-friendly manual. ML is the next big breakthrough in technol
  • Width: 191 mm
  • ISBN-10: 1782161406
  • Publisher Date: 28 Mar 2013
  • Binding: Paperback
  • Height: 235 mm
  • No of Pages: 290
  • Spine Width: 15 mm
  • Weight: 503 gr


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