Designed to take you on a guided tour of the most relevant and powerful machine learning techniques in use today by top data scientists, this book is just what you need to push your Python algorithms to maximum potential. Clear examples and detailed code samples demonstrate deep learning techniques, semi-supervised learning, and more - all whilst working with real-world applications that include image, music, text, and financial data.


The machine learning techniques covered in this book are at the forefront of commercial practice. They are applicable now for the first time in contexts such as image recognition, NLP and web search, computational creativity, and commercial/financial data modeling. Deep Learning algorithms and ensembles of models are in use by data scientists at top tech and digital companies, but the skills needed to apply them successfully, while in high demand, are still scarce.

This book is designed to take the reader on a guided tour of the most relevant and powerful machine learning techniques. Clear descriptions of how techniques work and detailed code examples demonstrate deep learning techniques, semi-supervised learning and more, in real world applications. We will also learn about NumPy and Theano.

By this end of this book, you will learn a set of advanced Machine Learning techniques and acquire a broad set of powerful skills in the area of feature selection & feature engineering.

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Spis treści

Advanced Machine Learning with Python. Solve challenging data science problems by mastering cutting-edge machine learning techniques in Python eBook -- spis treści

• 1. Unsupervised machine learning
• 2. Deep Belief Networks
• 3. Stacked Denoising Autoencoders
• 4. Convolutional Neural Networks
• 5. Semi supervised learning
• 6. Text Feature Engineering
• 7. Feature Engineering (continued)
• 8. Ensemble Methods
• 9. Additional Python Machine Learning Tools
• 10. Appendix A