Python Machine Learning, 1st Edition
Raschka, Sebastian
Verkauft von Mahler Books, PFLUGERVILLE, TX, USA
AbeBooks-Verkäufer seit 15. Februar 2005
Gebraucht - Softcover
Zustand: Very Good
Anzahl: 1 verfügbar
In den Warenkorb legenVerkauft von Mahler Books, PFLUGERVILLE, TX, USA
AbeBooks-Verkäufer seit 15. Februar 2005
Zustand: Very Good
Anzahl: 1 verfügbar
In den Warenkorb legenThis book is in very good condition; no remainder marks. It does have some shelfwear scratching. Inside pages are clean. ; 454 pages.
Bestandsnummer des Verkäufers 10GW20-686-288f
Unlock deeper insights into Machine Leaning with this vital guide to cutting-edge predictive analytics
Key Features
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. Covering a wide range of powerful Python libraries, including scikit-learn, Theano, and Keras, and featuring guidance and tips on everything from sentiment analysis to neural networks, you'll soon be able to answer some of the most important questions facing you and your organization.
What you will learn
Who this book is for
If you want to find out how to use Python to start answering critical questions of your data, pick up Python Machine Learning - whether you want to get started from scratch or want to extend your data science knowledge, this is an essential and unmissable resource.
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