P R.E S E N T S              .

Mastering Machine Learning With Python In Six Steps

DATE: 2017-10-15  SIZE: 9.64 MB    DISKS: 2x 10MB     PAGES: n/a

PUBLISHER: Apress                           GENRE:

AUTHOR: Manohar Swamynathan

FORMAT: PDF   PROTECTION: DRM  EDITION: n/a

URL: https://is.gd/3wEYO0

LANGUAGE: English   ISBN: 9781484228661

: Master machine learning with Python in six steps and explore fundamental t :
: advanced topics, all designed to make you a worthy practitioner. This      :
: book's approach is based on the "Six degrees of separation" theory, which  :
: states that everyone and everything is a maximum of six steps away.        :
: Mastering Machine Learning with Python in Six Steps presents each topic in :
: two parts: theoretical concepts and practical implementation using suitabl :
: Python packages. You'll learn the fundamentals of Python programming       :
: language, machine learning history, evolution, and the system development  :
: frameworks. Key data mining/analysis concepts, such as feature dimension   :
: reduction, regression, time series forecasting and their efficient         :
: implementation in Scikit-learn are also covered. Finally, you'll explore   :
: advanced text mining techniques, neural networks and deep learning         :
: techniques, and their implementation. All the code presented in the book   :
: will be available in the form of iPython notebooks to enable you to try ou :
: these examples and extend them to your advantage. What You'll Learn Examin :
: the fundamentals of Python programming language Review machine Learning    :
: history and evolution Understand machine learning system development       :
: frameworks Implement supervised/unsupervised/reinforcement learning        :
: techniques with examples Explore fundamental to advanced text mining       :
: techniques Implement various deep learning frameworks Who This Book Is For :
: Python developers or data engineers looking to expand their knowledge or   :
: career into machine learning area. Non-Python (R, SAS, SPSS, Matlab or any :
: other language) machine learning practitioners looking to expand their     :
: implementation skills in Python. Novice machine learning practitioners     :
: looking to learn advanced topics, such as hyperparameter tuning, various   :
: ensemble techniques, natural language processing (NLP), deep learning, and :
: basics of reinforcement learning.                                          :

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