Low Light Image Enhancement Using Zero-DCE
Tutorial on Low light image enhancement usind Zero-DCE
Face Detection and Recognition with Python, OpenCV, and Deep Learning: A Step-by-Step Guide
Face Detection and Recognition with Python.
The process involved using MTCNN for face detection, InceptionResnetV1 to extract face embeddings, and an SVM classifier to identify the person based on those embedding
Azure MLOps for Beginners: Train, Deploy and Serve a GRU forecasting model.
Azure MLOps for Begineers: Train, Deploy and Serve a GRU forecasting model.
Building a Low-Light Image Enhancer with GLADNet in PyTorch
Low-Light Image Enhancer with GLADNet and Pytorch
Build an Image Classifier on Azure: VGG16, Hymenoptera Data, and Flask Deployment
Build an Image Classifier on Azure
Guide to Retinal Blood Vessel Segmentation with U-Net in PyTorch
Learning Image Segmentation with U-Net in Pytorch
Solving Bipedal Walker Hardcore Challenge with Soft Actor-Critic Algorithm
we will learn to solve Bipedal Walker Hardcore Challenge with Soft Actor-Critic Algorithm
Bipedal Walker with PPO: A Step-by-Step Guide to Solving the RL Challenge
In this tutorial we will learn how to master a Bipedal Walker with PPO (Proximal Policy Optimization).
Master Snake Game AI with PPO: Step-by-Step Guide (Part II)
Second Part we will learn about the major components PPO for ai agent.
Master Snake Game AI with PPO: Step-by-Step Guide (Part I)
This is first of two part tutorial. Here we learn to build snake game. In part two, we will learn to build a PPO agent to play with it.
PPO Implementation in PyTorch
In this blog post, we will explore the Proximal Policy Optimization (PPO) algorithm. We’ll compare it to other deep reinforcement learning algorithms like Double Deep Q-learning and TRPO. Additionally, we’ll learn how to implement PPO using PyTorch.
Prioritized Experience Replay Using PyTorch
Introduction of Prioritized Experience Replay and its implementation with PyTorch.
Policy Gradient Implementation Using PyTorch
This is an implementation of Policy Gradient algorithm using PyTorch.
Gaussian Double Deep Q Learning
Implementation of Gaussian Double Deep Q network with PyTorch
MoG-DQN Implementation In PyTorch To Solve Lunar Lander
This is implementation of MoG-DQN using PyTorch.
Understanding Implicit Quantile Networks in Reinforcement Learning
IQN is a state-of-the-art RL algorithm that focuses on predicting the full distribution of returns rather than just the mean. This approach provides a more comprehensive understanding of the value of actions, allowing for better decision-making in uncertain environments
Double DQN For Lunar Lander With PyTorch
In this blog post, we will implement Double DQN using PyTorch to solve the Lunar Lander environment from OpenAI Gym.
Acrobot-ing with Actor Critic
Solving the Acrobot problem with the help of Actor-Critic algorithm.
CNN and its friends in PyTorch
The blog about the CNN functions in PyTorch and other assisting functions generally used with Convolution Neural Networks.