Introduction to machine learning with python o reilly

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introduction to machine learning with python o reilly

Introduction to Machine Learning with Python: A Guide for Data Scientists by Andreas C. Muller

Machine learning has become an integral part of many commercial applications and research projects, but this field is not exclusive to large companies with extensive research teams. If you use Python, even as a beginner, this book will teach you practical ways to build your own machine learning solutions. With all the data available today, machine learning applications are limited only by your imagination.

Youll learn the steps necessary to create a successful machine-learning application with Python and the scikit-learn library. Authors Andreas Muller and Sarah Guido focus on the practical aspects of using machine learning algorithms, rather than the math behind them. Familiarity with the NumPy and matplotlib libraries will help you get even more from this book.

With this book, youll learn:

Fundamental concepts and applications of machine learning
Advantages and shortcomings of widely used machine learning algorithms
How to represent data processed by machine learning, including which data aspects to focus on
Advanced methods for model evaluation and parameter tuning
The concept of pipelines for chaining models and encapsulating your workflow
Methods for working with text data, including text-specific processing techniques
Suggestions for improving your machine learning and data science skills
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Published 07.10.2019

Humble Python Book by O'Reilly Bundle

Machine learning has become an integral part of many commercial applications and research projects, but this field is not exclusive to large companies with extensive research teams.
Andreas C. Muller

Introduction to Machine Learning Using Python

Machine Learning is about making predictions. This post will give an introduction to Machine Learning through a problem that most businesses face: predicting customer churn. ML can help predict which of your customers are at risk for leaving in advance, and give you an edge by pre-empting with action. Machine Learning allows us to accurately predict things using simple statistical methods, algorithms, and modern computing power. Churn Example: Machine Learning will help us understand why customers churn and when. Our input values might include:.

Note that while every book here is provided for free, consider purchasing the hard copy if you find any particularly helpful. In many cases you will find Amazon links to the printed version, but bear in mind that these are affiliate links, and purchasing through them will help support not only the authors of these books, but also LearnDataSci. Thank you for reading, and thank you in advance for helping support this website. Comprehensive, up-to-date introduction to the theory and practice of artificial intelligence. Number one in its field, this textbook is ideal for one or two-semester, undergraduate or graduate-level courses in Artificial Intelligence. Learning and Intelligent Optimization LION is the combination of learning from data and optimization applied to solve complex and dynamic problems.

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Data Science at the Command Line: Facing the Future with Time-Tested Tools

This list consists of articles, tutorials, blogs, and other interesting stuff related to data science — things that I find useful, and you may too. Note : You can directly right-click and open any link on this page, or download the HTML file from here and import this list as bookmarks in your favorite browser! How to deliver on Machine Learning projects — Insight Data. The body is the missing link for truly intelligent machines Aeon Ideas. The darker side of machine learning TechCrunch.


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