Basic program to demonstrate linear regression from scikit learn library. Requirements The following libraries should be installed before running the code. sklearn matplotlib pandas num...

Final part of the series is here. Hope you have enjoyed as much as I have enjoyed making this. We are now going to train our DQN model. System requirements :- TensorFlow : 2.4.1 Dedicated G...

Introduction to deep Q-learning. Deep Q-learning is the combination of deep learning and reinforcement learning. Here, we create a RL model with a neural network similar to that of in deep learnin...

This is a tutorial to create your own Q-learning environment. We need opencv for this, so make sure to ‘pip install’ it. We also need a python imaging library, called pillow, so also install that ...

In the previous program, our agent achieved its target. Now, we want to measure the metrics of its achievements. This will help us select the best Q-table for training a model under given circumsta...

Progressing on what we developed in the previous program, this one deals with the agent actually achieving its goal. We create multiple episodes for our agent to learn. Also, use of epsilon and it...

This is a program to open and explore a basic Q-learning environment. 💢 Environment setup We use the ‘gym’ library to open an environment called ‘MountainCar-v0”. It is a simple environment consi...

This guide deals deep Q-Learning after a certain point and so the python codes are written assuming that anyone following this is familiar with basic python programming, how to develop models, and ...

Introduction This guide will serve as an introduction to ANNs. We will build a neural network from scratch without using any specialised libraries like keras or pytorch. We will only use NumPy for...