An easy-to-understand explanation of Deep Q-Learning with PyTorch code implementation — Deep Reinforcement Learning Deep Reinforcement Learning combines Reinforcement Learning algorithms with Artificial Neural Networks. It allows the agent to learn an optimal policy for sequential decision problems by maximizing the cumulative future reward. Deep RL = RL Algorithm + Artificial Neural Network Reinforcement Learning is a goal-oriented algorithm where the agent aims to…

Notes-taking techniques I use for effective learning — There are several techniques for taking notes, and the best method depends on the types of notes you want to take. Notes are taken for a variety of purposes : Learning a new topic: Notes can be a helpful tool for learning and understanding new information. Long-term retention: Reviewing your…

A technical understanding of the ChatGPT from OpenAI, the most talked about AI chatbot of 2022. — What is ChatGPT? ChatGPT is an Artificial Intelligence software developed by OpenAI where people can ask questions, and the software will answer their questions based on context and relevance. To use ChatGPT, you can type a question here; ChatGPT will read the questions and generate appropriate responses in a…

A design pattern for Microservices to improve the stability and resiliency of Applications — You have a microservice to update different Item attributes for a retail outlet. …

Create a New Custom Environment using Open AI Gym — In this article, you will learn how to create a custom Environment using OpenAI Gym to train the Agent. Reinforcement learning maps observations to actions to maximize the long-term reward. The Agent explores the Environment and finds the actions for which the Environment yields the most rewards.

A design pattern to handle read workload efficiently — You need to design a product recommendation solution for an e-commerce site to handle high customer traffic with lower latency and quick response time. The recommendation must take care of the customer's previous purchases and items bought by other customers who are buying similar products and recommend new items. A…

Design your cloud application for high performance, better security, and scalability using Command and Query Responsibility Segregation (CQRS) design pattern. — Your Inventory application suffers from performance issues while updating the stock and also when the e-commerce site queries the item stock to check the item availability. The situation becomes terrible during peak shopping events. The performance issue of updating and querying the same data entity can be resolved using the…

An intuitive and simple understanding of the cloud computing design pattern for data consistency — You are designing an Inventory application with microservices using cloud infrastructure; your goal is to build a reliable, scalable, secure way to ensure data consistency across microservices in a distributed transaction. Is there a solution template that can apply to design microservices that maintain data consistency in a distributed transaction…

A practical guide to Microservices Architecture basics, best practices, and a use case. — Here you will learn What problem does Microservice plan to address? What is a Microservice? The key characteristic of Microservices A step-by-step use case for designing a Microservice Pros and Cons of Microservices Best Practices for designing Microservices Why Microservices? Before Microservices, applications followed a Monolithic pattern where processes like user interface…