An intuitive explanation of the terms used for On Policy and Off Policy, along with their differences — The explanation used in this article is to just simplify the concepts for understanding purpose. You just moved to a new locality and have tried a few restaurants in your area. Today you are going out to eat again at a restaurant. We are transforming the problem of selecting the…

An easy-to-understand explanation of the Monte-Carlo method for Reinforcement learning — In Reinforcement learning, the learner or the decision maker, called the Agent, constantly interacts with its Environment by performing actions sequentially at each discrete time step. Interaction of the Agent with its Environment changes the Environment's state, and as a result, the Agent receives a numerical reward from the Environment.

Learn about Generalized Policy Iteration, Value iteration, and Policy Iteration — Reinforcement learning is where the learner or the decision maker, called the Agent, interacts continually with its Environment by performing actions sequentially at each discrete time step. Interaction of the Agent with its Environment changes the Environment’s state, and as a result, the Agent receives a numerical reward from the…

The memoryless Markov Decision Process predicts the next state based only on the current state and not the previous one. — Google’s PageRank developed by Sergey Brin and Larry Page is based on a Markov Decision Process(MDP) utlizing the Markov chains making it the most used applications of a MDP. What is MDP? Markov Decision Process(MDP) is a mathematical framework for sequential decision and a dynamic optimization method in a stochastic discrete control process.

An intuitive explanation of Dynamic programming — What if you need to find the minimum number of coins that make up an amount with coins of different denominations? For example, if you are given 1 cent, 5 cents, and 10 cents and asked to use the minimum number of coins to make 18 cents. The example of…

Convert an audio file into a text file using Speech Recognition — Here you will save the audio from a microphone to a file and then transcribe the audio file to text using speech recognition. Audio is any sound in a range that the human ear can hear. Audio, voice, or music is recorded using a microphone and then saved to an…

Learn to create a QR Code and read the contents of the QR code using Python — What is a QR Code? QR Code was invented in 1994 by the Japanese automotive company Denso Wave QR stands for Quick Response to allow immediate access to the information hidden in the code and is a two-dimensional bar code consisting of black squares arranged in a square grid on a white background. QR code…

An easy-to-understand explanation of critical elements of Reinforcement learning — If you are trying to learn a new skill like roller skating, you will probably fall several times before mastering the art of skating. You will be rewarded a successful landing every time you learn to balance. Every time you are not able to balance yourself, you will receive a…

An Intuitive explanation of Supervised, Unsupervised, and Reinforcement learning along with the differences — Machine Learning(ML) is a subset of Artificial Intelligence(AI), defined as a computer's ability to learn from data by using algorithms to imitate intelligent human behavior of decision making and predictions. There are three main groups of algorithms in ML: Supervised learning, Unsupervised learning