In this tutorial, I will demonstrate how to use Google Colab (Google’s free cloud service for AI developers) to train the Yolo v3 custom object detector with free GPU

Is the training Process Smooth???

  1. While trying to connect to GPU…


In this tutorial, I’m going to explain to you an easy way to train YOLO v3 on TensorFlow 2 to detect a custom object even if you’re a beginner or if you have no experience with coding

1. Prepare the Image dataset


In this step-by-step tutorial, I will show how to train a 7-class object detector (could use this method to get a dataset for every detector you may use)


In this tutorial, I’ll cover the Yolo v3 loss function and model training. We’ll train a custom object detector on Mnist dataset


I will make Yolo v3 easy and reusable without over-complicating things. With this tutorial, you will be able to implement object detection in TensorFlow 2 simply


In this tutorial, we’ll solve the BipedalWalker-v3 environment, which is a very hard environment in the Gym. Our agent should run very fast, should not trip himself off, should use as little energy as possible…


In this step-by-step reinforcement learning tutorial with gym and TensorFlow 2. I’ll show you how to implement a PPO for teaching an AI agent how to land a rocket (Lunarlander-v2)


In this tutorial, we’ll dive into the understanding of the PPO architecture and we’ll implement a Proximal Policy Optimization (PPO) agent that learns to play Pong-v0


In this tutorial, I will provide an implementation of the Asynchronous Advantage Actor-Critic (A3C) algorithm in Tensorflow and Keras. We will use it to solve a simple challenge in the Pong environment


Today, we’ll study a Reinforcement Learning method that we can call a ‘hybrid method’: Actor-Critic. This algorithm combines the value optimization and policy optimization approaches

Rokas Balsys

Machine learning enthusiast

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