Low Light Image Enhancement Using Zero-DCE
Tutorial on Low light image enhancement usind Zero-DCE
Tutorial on Low light image enhancement usind Zero-DCE
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
In Part I for Azure MLOps for Begineers, we learnt how to train, register and deploy our model in Azure ML. In this part, we will learn how to use that endpoint to make forecast using a Flask Based web application. For basic Flask setup check : Streamlined Flask Deployment on Azure. We will build our forecasting application on the […]
Azure MLOps for Begineers: Train, Deploy and Serve a GRU forecasting model.
With Azure and GitHub CI/CD, you can automate your Flask deployment process for a seamless, instant launch. This powerful combination streamlines workflows, reduces manual effort, and ensures your web application is up and running in no time. In this guide, we’ll explore how to leverage GitHub CI/CD for rapid Flask deployment on Azure, empowering developers to deliver scalable, high-performance web apps with ease.
Low-Light Image Enhancer with GLADNet and Pytorch
Breast Cancer Classification with Azure ML & MLflow: End-to-End ML Tutorial
Build an Image Classifier on Azure
Learn to train, register and deploy model in Azure ML
This introduction focuses on using MLflow Tracking to experiment with a Support Vector Machine (SVM) classifier on the Digits dataset, a classic dataset in machine learning for multi-class classification.
Learning Image Segmentation with U-Net in Pytorch
In this tutorial we will learn how to master a Bipedal Walker with PPO (Proximal Policy Optimization).
Second Part we will learn about the major components PPO for ai agent.
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.
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.
Introduction of Prioritized Experience Replay and its implementation with PyTorch.
In this article we will learn how to use MySql with Django. Operating system used in this process in Ubuntu 22.04.
In this blog, we will learn how visualize data by combining the chart.js with Django. For this we will continue with our Django project from last post.
In Django Admin Customization we will look various ways to customize the admin panel of Django. We will also look how to add custom filters, how to use 3rd party packages to search and style. We will learn how to import and export our data and many more.
In this Django RESTful API we will learn to create a RESTful API with Django. Here we will Create, Read, Update and Delete posts using RESTful API. We will use the POSTMAN to test our API.