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+--- Thread: Real World 5+ Deep Learning Projects Complete Course (/Thread-Real-World-5-Deep-Learning-Projects-Complete-Course--695317)
Real World 5+ Deep Learning Projects Complete Course - AD-TEAM - 11-27-2024
![[Image: 6607a8b2dbc6246c7a74287957cfe949.jpg]](https://i124.fastpic.org/big/2024/1127/49/6607a8b2dbc6246c7a74287957cfe949.jpg)
Real World 5+ Deep Learning Projects Complete Course
Published 1/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 2.70 GB | Duration: 2h 15m
Learn Real World 5+ Deep Learning Projects Complete Course Using Roboflow and Google Colab
What you'll learn
Understand how to integrate Roboflow into the project workflow, leveraging its features for efficient dataset management, augmentation, and optimization for bot
Explore the process of collecting and preprocessing datasets for both facial recognition and emotion detection, ensuring the data is optimized for training a YO
Dive into the annotation process, marking facial features on images for recognition and labeling emotions for detection. Train YOLOv7 models for accurate and ro
Explore the end-to-end training workflow of YOLOv7 using the annotated and preprocessed datasets, adjusting parameters, and monitoring model performance for bot
Requirements
Access to a computer with internet connectivity.
Basic understanding of machine learning and computer vision concepts.
Description
Course Title: Real World 5+ Deep Learning Projects Complete Course Using Roboflow and Google ColabCourse Description:Welcome to the immersive "Learn Facial Recognition And Emotion Detection Using YOLOv7: Course Using Roboflow and Google Colab." In this comprehensive course, you will embark on a journey to master two cutting-edge applications of computer vision: facial recognition and emotion detection. Utilizing the powerful YOLOv7 algorithm and leveraging the capabilities of Roboflow for efficient dataset management, along with Google Colab for cloud-based model training, you will gain hands-on experience in implementing these technologies in real-world scenarios.What You Will Learn:Introduction to Facial Recognition and Emotion Detection:Understand the significance of facial recognition and emotion detection in computer vision applications and their real-world use cases.Setting Up the Project Environment:Learn how to set up the project environment, including the installation of necessary tools and libraries for implementing YOLOv7 for facial recognition and emotion detection.Data Collection and Preprocessing:Explore the process of collecting and preprocessing datasets for both facial recognition and emotion detection, ensuring the data is optimized for training a YOLOv7 model.Annotation of Facial Images and Emotion Labels
ive into the annotation process, marking facial features on images for recognition and labeling emotions for detection. Train YOLOv7 models for accurate and robust performance.Integration with Roboflow:Understand how to integrate Roboflow into the project workflow, leveraging its features for efficient dataset management, augmentation, and optimization for both facial recognition and emotion detection.Training YOLOv7 Models:Explore the end-to-end training workflow of YOLOv7 using the annotated and preprocessed datasets, adjusting parameters, and monitoring model performance for both applications.Model Evaluation and Fine-Tuning:Learn techniques for evaluating the trained models, fine-tuning parameters for optimal performance, and ensuring robust facial recognition and emotion detection.Deployment of the Models:Understand how to deploy the trained YOLOv7 models for real-world applications, making them ready for integration into diverse scenarios such as security systems or human-computer interaction.Ethical Considerations in Computer Vision:Engage in discussions about ethical considerations in computer vision, focusing on privacy, consent, and responsible use of biometric data in facial recognition and emotion detection. Overview
Section 1: Introduction To Real World 5+ Deep Learning Projects Complete Course
Lecture 1 Introduction To Brain Tumor Detection Using YOLOv8 Project
Lecture 2 ROBOFLOW ACCOUNT CREATION
Lecture 3 DATASET CREATION FOR BRAIN TUMOR DETECTION
Lecture 4 ANNOTATION AND LABELLING FOR DATASET
Lecture 5 TRAINING DATASET WITH YOLOv8 MODEL
Lecture 6 VALIDATE TRAINED MODEL
Lecture 7 PROJECT EXECUTION IN PYCHARM IDE
Section 2: INTRODUCTION TO EMOTION DETECTION USING YOLOv7 PROJECT
Lecture 8 INTRO TO COURSE
Lecture 9 EMOTION DETECTION CLASS ONE
Lecture 10 DATASET CREATION USING VIDEOS AND IMAGES
Lecture 11 ANNOTATION FOR DATASET
Lecture 12 TRAIN DATASET WITH YOLOV7 MODEL
Lecture 13 VALIDATE TRAINED MODEL
Lecture 14 PROJECT EXECUTION IN PYCHARM IDE
Section 3: INTRODUCTION TO FACE RECOGNITION USING YOLOv7 PROJECT
Lecture 15 INTRO TO PROJECT
Lecture 16 ACCOUNT CREATION
Lecture 17 DATASET CREATION USING VIDEOS AND IMAGES
Lecture 18 ANNOTATION FOR DATASET
Lecture 19 TRAINING THE DATASET WITH YOLOv7 MODEL
Lecture 20 VALIDATE MODEL IN ROBOFLOW
Lecture 21 PROJECT EXECUTION IN PYCHARM IDE
Section 4: INTRODUCTION TO HELMET DETECTION USING YOLOv7 PROJECT
Lecture 22 INTRO TO PROJECT
Lecture 23 ACCOUNT CREATION
Lecture 24 DATASET CREATION FOR HELMET DETECTION
Lecture 25 ANNOTATION FOR DATASET
Lecture 26 TRAINING YOLOV7 MODEL
Lecture 27 VALIDATE MODEL
Lecture 28 PROJECT EXECUTION IN PYCHARM IDE
Section 5: INTRODUCTION TO GOOGLE COLAB
Lecture 29 INTRO TO COURSE
Lecture 30 IMPORT PROJECT IN GOOGLE COLAB
Lecture 31 TRAINING YOLOV7 MODEL IN COLAB
Lecture 32 VALIDATE MODEL IN COLAB
Lecture 33 DOWNLOAD MODEL IN COLAB
Students and professionals in computer vision, artificial intelligence, or human-computer interaction.,Developers interested in mastering YOLOv7 for multiple computer vision applications.
![[Image: kBYq9Agb_o.jpg]](https://images2.imgbox.com/41/e7/kBYq9Agb_o.jpg)