Mastering Machine Learning with Python in Six Steps: A Practical Implementation Guide to Predictive Data Analytics Using Python, 1st Edition free ebook download.

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Mastering Machine Learning with Python in Six Steps: A Practical Implementation Guide to Predictive Data Analytics Using Python, 1st Edition free ebook download

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Programming

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Catalogue

Author(s):	Manohar Swamynathan

Date:	2017	Format:	pdf	Language:	English	ISBN/ASIN:	1484228650
Pages:	1	OCR:		Quality:		ISBN13:
Uploader:	tvladb77	Upload Date:	5/7/2020 11:00:35 PM

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Description: Click to see full description

Master machine learning with Python in six steps and explore fundamental to 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 suitable 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 out these examples and extend them to your advantage.
What You'll Learn

Examine 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.

Links Table

	Title	Link	Password	Size (MB)	Thank to	Inform Admin
2776499	Book	https://nitroflare.com/view/3186939138CA...	GetPremium2SupportMe	9.60	tvladb77

Tags: Analytics Data Guide Implementation Learning Machine Mastering Practical Predictive Python

Title	Link	Password	Size	Reason

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