Reinforcement Learning Tutorial | Reinforcement Learning Example Using Python | Edureka

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In this video on “Reinforcement Learning Tutorial” you will get an in-depth understanding about how reinforcement learning is used in the real world. I’ll be covering the following topics in this session:

(01:48) Introduction to Machine Learning
(05:51) What is Reinforcement Learning?
(06:55) Reinforcement Learning with an analogy
(07:54) Reinforcement Learning process
(08:57) Reinforcement Learning Counter-Strike example
(10:40) Reinforcement Learning Definitions
(13:01) Reinforcement Learning Concepts
(16:21) Markov’s Decision Process
(20:00) Understanding Q-Learning
(38:10) Demo

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About the Course

Edureka’s Data Science Course on Python helps you gain expertise in various machine learning algorithms such as regression, clustering, decision trees, random forest, Naïve Bayes and Q-Learning. Throughout the Data Science Certification Course, you’ll be solving real life case studies on Media, Healthcare, Social Media, Aviation, HR.

During our Python Certification Training, our instructors will help you to:



1. Master the basic and advanced concepts of Python

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3. Automate data analysis using python

4. Gain expertise in machine learning using Python and build a Real Life Machine Learning application

5. Understand the supervised and unsupervised learning and concepts of Scikit-Learn

6. Explain Time Series and it’s related concepts

7. Perform Text Mining and Sentimental analysis

8. Gain expertise to handle business in future, living the present

9. Work on a Real Life Project on Big Data Analytics using Python and gain Hands on Project Experience

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Why learn Python?



Programmers love Python because of how fast and easy it is to use. Python cuts development time in half with its simple to read syntax and easy compilation feature. Debugging your programs is a breeze in Python with its built in debugger. Using Python makes Programmers more productive and their programs ultimately better. Python continues to be a favorite option for data scientists who use it for building and using Machine learning applications and other scientific computations.

Python runs on Windows, Linux/Unix, Mac OS and has been ported to Java and .NET virtual machines. Python is free to use, even for the commercial products, because of its OSI-approved open source license.

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