Top 10 Books for Machine Learning | Best Machine Learning Books for Beginners And Advanced | Edureka

** Machine Learning Training: https://edureka.co/python **
This Edureka video on 'Top 10 Best Books for Machine Learning' will help you out if you are someone who loves to study from books. We have suggestions for the best books for beginners to advanced programmers who look to get started or learn something much more in the field of Machine Learning.
The video has been broken down in the following segments:
What is Machine Learning?
Beginner Books for Machine Learning
Advanced Books for Machine Learning

Links to all the Machine Learning books are here:
Machine Learning For Absolute Beginners: https://www.amazon.in/Machine-Learning-Absolute-Beginners-Introduction/dp/1549617214/
Machine Learning For Dummies: https://www.amazon.in/Machine-Learning-Python-R-Dummies/dp/8126563052
Artificial Intelligence: A Modern Approach: https://www.amazon.in/Artificial-Intelligence-3e-Modern-Approach/dp/9332543518
Machine Learning in Action: https://www.amazon.in/Machine-Learning-Action-Peter-Harrington/dp/9350044137
Machine Learning for Hackers: https://www.amazon.in/Machine-Learning-Hackers-Studies-Algorithms/dp/9350236745

Python Machine Learning: https://www.amazon.in/Python-Machine-Learning-Sebastian-Raschka/dp/1787125939
Data Science from Scratch: https://www.amazon.in/Data-Science-Scratch-Principles-Python/dp/9352138325
Programming Collective Intelligence: https://www.amazon.in/Programming-Collective-Intelligence-Building-Applications/dp/8184043708
Make Your Own Neural Network: https://www.amazon.in/Make-Your-Own-Neural-Network/dp/1530826608
Pattern Recognition and Machine Learning: https://www.amazon.in/Pattern-Recognition-Learning-Information-Statistics/dp/0387310738

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How it Works?

1. This is a 5 Week Instructor led Online Course,40 hours of assignment and 20 hours of project work

2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course.

3. At the end of the training you will be working on a real time project for which we will provide you a Grade and a Verifiable Certificate!


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About the Course


Edureka’s Machine Learning Course using Python is designed to make you grab the concepts of Machine Learning. The Machine Learning training will provide deep understanding of Machine Learning and its mechanism. As a Data Scientist, you will be learning the importance of Machine Learning and its implementation in python programming language. Furthermore, you will be taught Reinforcement Learning which in turn is an important aspect of Artificial Intelligence. You will be able to automate real life scenarios using Machine Learning Algorithms. Towards the end of the course, we will be discussing various practical use cases of Machine Learning in python programming language to enhance your learning experience.


After completing this Machine Learning Certification Training using Python, you should be able to:

Gain insight into the 'Roles' played by a Machine Learning Engineer

Automate data analysis using python

Describe Machine Learning

Work with real-time data

Learn tools and techniques for predictive modeling

Discuss Machine Learning algorithms and their implementation

Validate Machine Learning algorithms

Explain Time Series and it’s related concepts

Gain expertise to handle business in future, living the present


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Why learn Machine Learning with Python?


Data Science is a set of techniques that enables the computers to learn the desired behavior from data without explicitly being programmed. It employs techniques and theories drawn from many fields within the broad areas of mathematics, statistics, information science, and computer science. This course exposes you to different classes of machine learning algorithms like supervised, unsupervised and reinforcement algorithms. This course imparts you the necessary skills like data pre-processing, dimensional reduction, model evaluation and also exposes you to different machine learning algorithms like regression, clustering, decision trees, random forest, Naive Bayes and Q-Learning.


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