Reinforcement Learning Tutorial | Reinforcement Learning Example Using Python | Edureka

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🔥 Post Graduate Diploma in Artificial Intelligence by E&ICT Academy
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

----------𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐏𝐲𝐭𝐡𝐨𝐧 𝐓𝐫𝐚𝐢𝐧𝐢𝐧𝐠𝐬-----------

----------𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐌𝐚𝐬𝐭𝐞𝐫𝐬 𝐏𝐫𝐨𝐠𝐫𝐚𝐦----------

-----------𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐔𝐧𝐢𝐯𝐞𝐫𝐬𝐢𝐭𝐲 𝐏𝐫𝐨𝐠𝐫𝐚𝐦----------

🌕Post Graduate Diploma in Artificial Intelligence Course offered by E&ICT Academy

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 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

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

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.

Python has evolved as the most preferred Language for Data Analytics and the increasing search trends on python also indicates that Python is the next "Big Thing" and a must for Professionals in the Data Analytics domain.

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That's why I love scratch implementation rather than using high end library, good job

wolfisraging

Edureka is the modern education system ! We love you, keep on the great work specially the free content !

murtuza.chawala

Best tutorial for reinforcement learning, well done. Thank u so much

wolfisraging

brilliant!! A perfect intro to ML. Well done Edureka!!

prasadgvs

This video is better than Udacity nano degree ml program class on Reinforcement learning

anintrovert

This is the most beautiful think Ive seen today :)

ratangles

This is one of the best lecture i have got to understand the crux of Q learning, ,hats off to you mam

bilalsadiq

One of the bestest learning source I have ever seen 🙄

kanchan

Amazing video. Very well done, u managed to introduce a very technical matter into simple words. Tx for sharing

fathialwosaibi

it was really a great explanation . Thank you so much

rohitshaw

I have never seen like this lecture in my entire life .expecting more video like this thank you

hidayatzeb

Well done. I really understood this in 30 minutes after going through bunch of notes and maths without really understand what was happening. Thanks very much

UlrichArmel

I really appreciated the explanation and that you didn't use any ML-libraries. But in my case, where you have two objects, which randomly spawn on a grid-map at the beginning of the "Game". One object (the "agent") has to reach the other object ("the goal"). But I can't create a matching matrix in this kind of problem, right? So, how should I deal with it?

spamspamer

Happy with the explanation. Thank you so much .😊

rekhars

Very good lecture, whoever was playing CS is a very good

ANIMESHKUMARPGP-

Very Useful and easy to understand - brilliant teacher, thank you !!

raginisharma

Excellent and this is amazing to go through your video good job

bhargavamahesh

Very nicely explained, best tutorial ill show to my university also how edureka teaches

jimable

You explained it all in 46minutes. Thanks a lot!

guillaumenelson

Nice explanation. Short, accurate and practical.

paichethan

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Reinforcement Learning Tutorial | Reinforcement Learning Example Using Python | Edureka