YOLO v4 and TF 2.0 by Nandakishor M

YOLO v4 and TF 2.0 Udemy

Friends, this time we are going to share an excellent option to perfect your professional skills. YOLO v4 and TF 2.0 by Nandakishor M is the most sought after course by users and one of the most popular on Udemy, the best online course platform.

YOLO v4 and TF 2.0 by Nandakishor M

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About the author Nandakishor M

Data scientist currently working in Deep learning. Developing AI-based robots and android apps for edge and cloud-based applications. Training students to understand concepts in CNN, image processing, computer vision, TensorFlow, YOLO and helping them in rapid prototyping projects. Running a small start-up with a mission to make a happy world

Udemy YOLO v4 and TF 2.0 course description

Hi everyone, Welcome to my second course on computer vision. In this course, you will understand the two most latest State Of The Art(SOTA) object detection architecture, which is YOLOv4 and TensorFlow 2.0 and its training pipeline. I also included a one-time labeling strategy , so that you won’t have to re-label the image for TensorFlow training. The course is split into 9 parts. Anaconda installation. Image dataset resizing. Image dataset labeling. YOLO to PASCAL VOC conversion for TF2.0 training. YOLOv4 training and tflite conversion on Google Colab. YOLOv4 Android deployment . SSD Mobilenet TF2.0 training and tflite conversion on Google Colab. SSD Mobilenet Android deployment . YOLOv4 and SSD technical details. Which include Basics Precision  and Recall IoU(Intersection Over Union) Mean Average Precision/Average Precision(mAP/AP) Batch Normalization Residual blocks Activation function Max pooling Feature Pyramid Networks(FPN) Path Aggregation Network (PAN) SPP (spatial pyramid pooling layer) Channel Attention Module(CAM) and Spatial Attention Module (SAM) YOLOv4 – Technical details Backbone Cross-Stage-Partial-connections (CSP) YOLO with SPP PAN in YOLOv4 Spatial Attention Module (SAM) in YOLOv4 Bag of freebies (Bof) and Bag of specials (BoS) SSD – Technical details Architecture overview and working Loss functions YOLO vs SSD Speed and accuracy benchmarking

YOLO v4 and TF 2.0 Info:

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What is included in this Udemy course?

Training YOLOv4 and TensorFlow 2.0 custom object detector on Google Colab with one-time labeling Deploying the trained models as an android app with real-time inference Image annotation and conversion of YOLO format to PASCAL VOC format Technical details of YOLOv4 and SSD Mobilenet with benchmarking

What do I need to do this course?

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