Complete Machine Learning Course > Projects

Reinforcement Learning Project - Teach a Taxi Part 3

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four types of reinforcement:

  • Positive reinforcement
  • negative reinforcement
  • extinction
  • punishment.
#BBD0E0 »

A reinforcement learning system has four primary components, in addition to the agent and the environment: a policy, a reward, a value function, and, optionally, a model of the environment. A policy describes how an agent acts at a specific point in time.

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Overall Rating

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Y
yogesh bandewar
4

where is dataset of this

S
Sanjeev raut
5

gooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooodddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddd

V
Vamsi Goud
5

Good

A
Ayush tomar
4

where are datasets of all this available

A
Abdul Salam
5

This one is one of the best online free source to study the coding or any particular course.

H
happy
4

Course is nice but where is the link for installation of Anaconda

D
Digvijay Kewale
4

Course is good understandable but I am not able to download resources (one star less only for this not able to download resources)

S
Shivendra Shahi
5

I am impresses by the way of teaching, what a magical teaching skill he has.

S
Sandeep Kumar
5

good content with free of cost

Sucheta Kumari
5

Course content and explanation method is just awesome. I like the way they presenting and specially at the end of each video content they feeding next intro content which makes motivated, excited .

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  1. Introduction to Machine Learning
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  2. Environment Setup Part 1
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  3. Environment Setup Part 2
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  4. Environment Setup Part 3
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  1. Data Wrangling in Machine Learning
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  2. Importing Libraries and Dataset in Machine Learning
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  3. Handling Missing Data in Machine Learning
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  4. Handling Missing Data in Machine Learning - Practical
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  5. Encoding Categorical Data in Machine Learning
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  6. Encoding Categorical Data in Machine Learning - Practical
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  7. Splitting Dataset in Machine Learning
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  8. Splitting Dataset in Machine Learning - Practical
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  9. Normalizing the Data in Machine Learning - Part 1
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  10. Normalizing the Data in Machine Learning - Part 2
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  11. Finding Machine Learning Datasets
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  12. Exploratory Data Analysis in Machine Learning
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  13. Plotting Graphs in Machine Learning - Part 1
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  14. Plotting Graphs in Machine Learning - Part 2
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  15. Distribution Models in Machine Learning - Part 1
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  16. Distribution Models in Machine Learning - Part 2
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  17. Assignment : Data Preprocessing for Machine Learning
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  1. Machine Learning Paradigms
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  2. Assignment : Machine Learning Paradigms
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  1. Overview of Classification
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  2. Logistic Regression in Machine Learning
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  3. Logistic Regression in Machine Learning - Practical - 1
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  4. Logistic Regression in Machine Learning - Practical - 2
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  6. KNN in Machine Learning Practical - 1
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  7. KNN in Machine Learning - Practical 2
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  9. Decision Trees for Classification in Machine Learning - Practical - 1
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  10. Decision Trees for Classification in Machine Learning - Practical - 2
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  17. Naive Bayes Classifier in Machine Learning Practical - 1
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  18. Naive Bayes Classifier in Machine Learning Practical - 2
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  19. Evaluating Classification Models Performance in Machine Learning
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  20. Evaluating Classification Models Performance in Machine Learning Practical
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  10. Decision Tree Regressor in Machine Learning Practical - 1
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  11. Decision Tree Regressor in Machine Learning Practical - 2
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  13. Evaluating Regression Model Performance in Machine Learning
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  14. Evaluating Regression Model Performance in Machine Learning - Practical
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  15. Assignment : Regression Algorithms
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  3. K-Means Clustering in Machine Learning - Practical
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  6. Agglomerative Clustering in Machine Learning - Practical
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  1. Reinforcement Learning Project - Teach a Taxi Part 1
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  2. Reinforcement Learning Project - Teach a Taxi Part 2
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  3. Reinforcement Learning Project - Teach a Taxi Part 3
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  4. Reinforcement Learning Project - Teach a Taxi Part 4
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  1. Interview Questions Part 1
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  2. Interview Questions Part 2
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  3. Interview Questions Part 3
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