Q-learn: solving Knight and Princess problem from scratch with Q-learn algorithm

This is another post on Q-learning reinforcement algorithm. Here we will understand and implement the Knight & Princess problem from the scratch using Python language, where the Knight need to move to the place of Princess ignoring the enemies on its way. In this post I have not used any third party library such as gym. Read more…

Understanding Q-learning algorithm with example using Python

Q-learning is a reinforcement learning technique in Machine learning used to answer the question “what action to take under what circumstances”. This model-free machine learning technique is used mainly in implementing any finite Markov Decision Process. The application of reinforcement learning technique can be found in traffic light control, robotics, recommendation system, gaming etc.
Before knowing Q-learning algorithm, let’s first understand the motivation behind this. What kind questions can be answered by Q-learning algorithm? Read more…

Difference between Classification and Clustering in Machine Learning

What is it?
Given a set of historical/old data along with their class name and a set of new data, classification is the process of assigning each new data with class name that is obtained from the old/historical data. 
Given a set of samples/data, clustering is the process of grouping the data based on their similarities and the patterns of the data.
Type of input data
Set of data with label/class name
Only the data set. No labeling is required.
  • A set of samples or data
  • A set of classes
A set of samples

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