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Introduction to Object Detection

Getting Started Introduction Why Is Object Detection Important?Types of Object Detection Algorithms Why Is YOLO So Popular?

Fundamentals for Understanding YOLO

Basics of the Convolutional Neural Network (CNN): Part I Basics of Convolutional Neural Network (CNN: Part II Understanding IoU (Intersection over Union)/Jaccard Index Understanding NMS (Non-Maximum Suppression)Understanding Anchor Boxes: Part I Understanding Anchor Boxes: Part II Bounding Box Predictions A Summary of How YOLO Makes Predictions What Is Overfitting in Object Detection?Batch Normalization (BN)Optimizers in YOLO Understanding Learning Rate (LR) Schedulers mAP Scores as Performance Metrics Understanding Loss Calculation Exercise: Build Your Own CNN Quiz

Project

Building a System for Safety Helmet Detection Based on YOLOv5

YOLOv7 Architecture

The Structure of YOLO (Backbone, Neck, and Head)Evolution of YOLO Models How does YOLO Handle Multi-Scale Predictions Understanding the YOLOv7 Model Structure Extended Efficient Layer Aggregation Networks (E-ELANs)Model Scaling for Concatenation-Based Models Trainable Bag-of-Freebies in YOLOv7 Decoding YOLOv8: A High-Level Overview Exercise (Designing a Darknet-19 Architecture)Exercise Solution Quiz

Improving Model Performance: Handling Overfitting/Underfitting

Why Is Data Augmentation Important?Exercise: Using the Albumentations Library for Augmentations Adding Background Images to Reduce False Positives Adding Synthetic Data to Our Dataset

Project

Dealing With Small Datasets In ML

Pre-Trained Models, Fine-Tuning, and Hyperparameters in OD

Pretrained Models and Transfer Learning in YOLO

Introduction to Fine-Tuning and Hyperparameters

The Role of Hyperparameters in YOLO

Quiz: Practical Scenarios

Mini Project

Sun Detection Using YOLOv8

Conclusion

Deep Dive into Object Detection with YOLO

The Role of Hyperparameters in YOLO

Understand some of the hyperparameters that are mostly modified in YOLO.

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Hyperparameters play a pivotal role in the training and fine-tuning of machine learning models, ...

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