Research Catalog
Advanced machine learning with Python : solve challenging data science problems by mastering cutting-edge machine learning techniques in Python
- Title
- Advanced machine learning with Python : solve challenging data science problems by mastering cutting-edge machine learning techniques in Python / John Hearty.
- Author
- Hearty, John
- Publication
- Birmingham, UK : Packt Publishing, 2016.
- ©2016
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1 Item
Status | Format | Access | Call Number | Item Location |
---|---|---|---|---|
Not available - Please for assistance. | Text | Request in advance | QA76.73.P98 H43 2016g | Off-site |
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Details
- Description
- xii, 254 pages : illustrations; 24 cm
- Summary
- The machine learning techniques covered in this book are at the forefront of commercial practice such as image recognition, NLP and web search, computational creativity and commercial/financial data modeling. Deep learning algorithms and ensembles of models are in the use by data scientists at top tech and digital companies. 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 the end of this book, you will have learned a set of advanced machine learning techniques and acquire a broad set of powerful skills in the area of feature selection and feature engineering.
- Subject
- Bibliography (note)
- Includes bibliographical references and an index.
- Contents
- Unsupervised Machine Learning -- Deep Belief Networks -- Stacked Denoising Autoencoders -- Convolutional Neural Networks -- Semi-Supervised Learning -- Text Feature Engineering -- Feature Engineering Part II -- Ensemble Methods -- Additional Python Machine Learning Tools
- ISBN
- 1784398632
- 9781784398637
- LCCN
- 99978877736
- OCLC
- ocn948336349
- 948336349
- SCSB-9229719
- Owning Institutions
- Columbia University Libraries