Deep Learning Object Detection by Training & Deploying YOLOX
Deep Learning Object Detection by Training & Deploying YOLOX, available at $64.99, has an average rating of 4.33, with 23 lectures, based on 8 reviews, and has 134 subscribers.
You will learn about 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++ This course is ideal for individuals who are Beginner Python Developers curious about applying deep learning techniques like YOLO or Software developers interested in using A.I and deep learning for object detection or Students interested in learning about object detection and how it can be applied practically or AI Practitioners wanting to master how to deploy AI Models to the cloud very easily or Software developers who want to learn how state of art object detection models are built and trained using deep learning. or Students who study different Object Detection Algorithms and want to Train YOLO with Custom Data. or Students who study Computer Vision and want to know how to use YOLO and its variants like YOLOX for Object Detection It is particularly useful for Beginner Python Developers curious about applying deep learning techniques like YOLO or Software developers interested in using A.I and deep learning for object detection or Students interested in learning about object detection and how it can be applied practically or AI Practitioners wanting to master how to deploy AI Models to the cloud very easily or Software developers who want to learn how state of art object detection models are built and trained using deep learning. or Students who study different Object Detection Algorithms and want to Train YOLO with Custom Data. or Students who study Computer Vision and want to know how to use YOLO and its variants like YOLOX for Object Detection.
Enroll now: Deep Learning Object Detection by Training & Deploying YOLOX
Summary
Title: Deep Learning Object Detection by Training & Deploying YOLOX
Price: $64.99
Average Rating: 4.33
Number of Lectures: 23
Number of Published Lectures: 23
Number of Curriculum Items: 23
Number of Published Curriculum Objects: 23
Original Price: $89.99
Quality Status: approved
Status: Live
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++
Who Should Attend
- Beginner Python Developers curious about applying deep learning techniques like YOLO
- Software developers interested in using A.I and deep learning for object detection
- Students interested in learning about object detection and how it can be applied practically
- AI Practitioners wanting to master how to deploy AI Models to the cloud very easily
- Software developers who want to learn how state of art object detection models are built and trained using deep learning.
- Students who study different Object Detection Algorithms and want to Train YOLO with Custom Data.
- Students who study Computer Vision and want to know how to use YOLO and its variants like YOLOX for Object Detection
Target Audiences
- Beginner Python Developers curious about applying deep learning techniques like YOLO
- Software developers interested in using A.I and deep learning for object detection
- Students interested in learning about object detection and how it can be applied practically
- AI Practitioners wanting to master how to deploy AI Models to the cloud very easily
- Software developers who want to learn how state of art object detection models are built and trained using deep learning.
- Students who study different Object Detection Algorithms and want to Train YOLO with Custom Data.
- Students who study Computer Vision and want to know how to use YOLO and its variants like YOLOX for Object Detection
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:
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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!!!
Course Curriculum
Chapter 1: Introduction
Lecture 1: Welcome
Lecture 2: General Introduction
Lecture 3: About this Course
Lecture 4: Link to code
Chapter 2: Theoritical background
Lecture 1: Haar Cascades and Histogram of gradients
Lecture 2: Convolutional Neural Networks
Lecture 3: RCNN,FastRCNN, FaterRCNN
Chapter 3: Single Stage Algorithms
Lecture 1: Understanding YOLO (You Only look once)
Lecture 2: Understanding YOLOX
Chapter 4: Dataset Preparation
Lecture 1: Pascal VOC dataset
Lecture 2: Preparing a custom dataset with Remo
Lecture 3: Preparing a custom dataset with LabelImg
Lecture 4: Assignment
Chapter 5: Finetuning and Testing
Lecture 1: Testing and FInetuning on Custom Dataset
Lecture 2: Wandb integration
Lecture 3: Running inference on Onnx model
Lecture 4: Assignment
Chapter 6: Deployment
Lecture 1: Understanding how APIs work
Lecture 2: Building an API with Fastapi
Lecture 3: Deploying on heroku
Lecture 4: Load testing with Locust
Lecture 5: Integration with C++
Lecture 6: Assignment
Instructors
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Neuralearn Dot AI
Helping millions of learners, master Deep Learning.
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- 3 stars: 2 votes
- 4 stars: 1 votes
- 5 stars: 5 votes
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