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Deep Learning Object Detection by Training & Deploying YOLOX
Finetuning and testing a YOLOX model on custom built dataset. Creating and deploying object detection API to cloud
This Course Includes
udemy
4.4 (6 reviews )
7 total hours 
english
Online - Self Paced
course
Udemy
About Deep Learning Object Detection by Training & Deploying YOLOX
Object detection algorithms are everywhere. With creation of much more efficient models from the early 2010s, these algorithms which now are built using deep learning models are achieving unprecedented performances.
In this course, we shall take you through an amazing journey in which you'll master different concepts with a step by step approach. We shall start from understanding how object detection algorithms work, to deploying them to the cloud, while observing best practices.
You will learn:
Pre-deep learning object detection algorithms like Haarcascades
Deep Learning algorithms like Convolutional neural networks, YOLO and YOLOX
Object detection labeling formats like Pascal VOC.
Creation of a custom dataset with Remo
Conversion of our custom dataset to the Pascal VOC format.
Finetuning and testing YOLOX model with custom dataset
Conversion of finetuned model to Onnx format
Experiment tracking with Wandb
How APIs work and building your own API with Fastapi
Deploying an API to the Cloud
Load testing a deployed API with Locust
Running object detection model in c++
If you are willing to move a step further in your career, this course is destined for you and we are super excited to help achieve your goals!
This course is offered to you by Neuralearn. And just like every other course by Neuralearn, we lay much emphasis on feedback. Your reviews and questions in the forum, will help us better this course. Feel free to ask as many questions as possible on the forum. We do our very best to reply in the shortest possible time.
Enjoy!!!
What You Will Learn?
- Master the basics of Object detection.
- Understanding pre-deep learning algorithms like haarcascades.
- Understanding deep learning algorithms like YOLO and YOLOX.
- Create your own dataset with Remo.
- Understanding the Pascal VOC dataset.
- Convert your custom dataset to Pascal VOC Format.
- Testing and training YOLOX model on custom dataset.
- Integrating Wandb for experiment tracking.
- Converting trained model to Onnx format.
- Understanding how APIs work.
- Building Object detection API with Fastapi.
- Deploying API to the Cloud.
- Load testing the API with Locust.
- Running the object detection model in c++.