Python Machine Learning - Free PDF Download

Book Description
Machine learning and predictive analytics are transforming the way businesses and other organizations operate. Being able to understand trends and patterns in complex data is critical to success, becoming one of the key strategies for unlocking growth in a challenging contemporary marketplace. Python can help you deliver key insights into your data – its unique capabilities as a language let you build sophisticated algorithms and statistical models that can reveal new perspectives and answer key questions that are vital for success.

Python Machine Learning gives you access to the world of predictive analytics and demonstrates why Python is one of the world's leading data science languages. If you want to ask better questions of data, or need to improve and extend the capabilities of your machine learning systems, this practical data science book is invaluable.

Table of Contents
1. Giving Computers the Ability to Learn from Data
2. Training Machine Learning Algorithms for Classification
3. A Tour of Machine Learning Classifiers Using Scikit-learn
4. Building Good Training Sets – Data Preprocessing
5. Compressing Data via Dimensionality Reduction
6. Learning Best Practices for Model Evaluation and Hyperparameter Tuning
7. Combining Different Models for Ensemble Learning
8. Applying Machine Learning to Sentiment Analysis
9. Embedding a Machine Learning Model into a Web Application
10. Predicting Continuous Target Variables with Regression Analysis
11. Working with Unlabeled Data – Clustering Analysis
12. Training Artificial Neural Networks for Image Recognition
13. Parallelizing Neural Network Training with Theano

You can download this book from any of the following links. If any link is dead please feel free to leave a comment.
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16 July 2016 at 01:33

This link is not working

21 July 2016 at 01:01

The link is dead. Can you look in to the issue.

21 July 2016 at 18:35

link has been updated

27 July 2016 at 18:18


9 August 2016 at 02:45

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20 August 2016 at 16:48

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4 December 2016 at 18:51

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6 December 2016 at 16:48

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