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Python Real World Machine Learning: Real World Machine...

Python Real World Machine Learning: Real World Machine Learning: Take your Python Machine learning skills to the next level

Joshi, Prateek, Massaron, Luca, Hearty, John
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Learn to solve challenging data science problems by building powerful machine learning models using Python. Machine learning is increasingly spreading in the modern data-driven world. It is used extensively across many fields such as search engines, robotics, self-driving cars, and more. Machine learning is transforming the way we understand and interact with the world around us. In the first module, Python Machine Learning Cookbook, you will learn how to perform various machine learning tasks using a wide variety of machine learning algorithms to solve real-world problems and use Python to implement these algorithms. The second module, Advanced Machine Learning with Python, is designed to take you on a guided tour of the most relevant and powerful machine learning techniques and you’ll acquire a broad set of powerful skills in the area of feature selection and feature engineering. The third module in this learning path, Large Scale Machine Learning with Python, dives into scalable machine learning and the three forms of scalability. It covers the most effective machine learning techniques on a map reduce framework in Hadoop and Spark in Python. This Learning Path will teach you Python machine learning for the real world. The machine learning techniques covered in this Learning Path are at the forefront of commercial practice. This Learning Path combines some of the best that Packt has to offer in one complete, curated package. It includes content from the following Packt products: Python Machine Learning Cookbook by Prateek Joshi Advanced Machine Learning with Python by John Hearty Large Scale Machine Learning with Python by Bastiaan Sjardin, Alberto Boschetti, Luca Massaron
Tahun:
2017
Edisi:
1
Penerbit:
Packt Publishing
Bahasa:
english
Halaman:
956
ISBN 10:
1787123219
ISBN 13:
9781787123212
Fail:
PDF, 17.17 MB
IPFS:
CID , CID Blake2b
english, 2017
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