Name of the book: Machine Learning with Python
Author: Andreas C. Mueller and Sarah Guido
Format: pdf, fb2, epub
The size: 30 MB, 28 MB, 10 MB
Description of book «Machine Learning with Python» (2016):
Python has become the lingua franca for many data science applications. It combines the powers of general purpose programming languages with the ease of use of domain specific scripting languages like matlab or R.
Python has libraries for data loading, visualization, statistics, natural language processing, image processing, and more. This vast toolbox provides data scientists with a large array of general and special purpose functionality.
As a general purpose programming language, Python also allows for the creation of complex graphic user interfaces (GUIs), web services and for integration into existing systems.
What this book will cover
In this book, we will focus on applying machine learning algorithms for the purpose of solving practical problems. We will focus on how to write applications using the machine learning library scikit-learn for the Python programming language. Important aspects that we will cover include formulating tasks as machine learning problems, preprocessing data for use in machine learning algorithms, and choosing appropriate algorithms and algorithmic parameters.
We will focus mostly on supervised learning techniques and algorithms, as these are often the most useful ones in practice, and they are easy for beginners to use and understand.
We will also discuss several common types of input, including text data.
Table of Contents:
- Supervised Learning
- Unsupervised Learning and Preprocessing
- Summary of scikit-learn methods and usage
- Representing Data and Engineering Features
- Model evaluation and improvement
- Algorithm Chains and Pipelines
- Working with Text Data
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