Published 11/2024
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 530.47 MB | Duration: 1h 19m
Learn Complete 5 ResNet Deep Learning Project From Scratch
What you'll learn
Understanding ResNet architecture
Preparing and augmenting datasets
Fine-tuning ResNet for various applications.
Evaluating model performance with metrics and techniques.
Requirements
Basic Python & Deep Learning Is Required
Description
Dive deep into the world of deep learning with the "Complete 5 ResNet Deep Learning Projects From Scratch" course! This hands-on course is designed to guide you through building five practical projects using ResNet (Residual Networks), a revolutionary deep learning architecture known for its accuracy and efficiency in solving complex image recognition tasks.Starting with the fundamentals of ResNet, you'll explore its architecture and understand the importance of residual connections in overcoming vanishing gradient issues. Each project will tackle real-world problems, taking you step-by-step through data preprocessing, model building, training, evaluation, and deployment.Projects Covered:Image Classification: Build a ResNet model for multi-class image classification tasks.Object Detection: Integrate ResNet with YOLO or similar frameworks for object detection.Medical Image Analysis: Develop a ResNet model for detecting diseases from medical imaging datasets.Image Segmentation: Use ResNet as a backbone for segmenting objects in complex images.Facial Recognition System: Train a ResNet model for accurate facial recognition.This course is ideal for:AI and Machine Learning Practitioners: Professionals seeking hands-on experience in applying ResNet to real-world problems.Software Developers: Developers wanting to transition into AI or enhance their skills in computer vision projects.Data Scientists: Experts looking to expand their knowledge of ResNet for image analysis and related applications.By the end, you'll have a robust understanding of ResNet and the ability to implement it in diverse applications.
Overview
Section 1: Introduction To Facial Image Prediction Project Using ResNet
Lecture 1 Introduction To Project
Lecture 2 Face Class 1 : Import Packages
Lecture 3 Face Class 2 : Import Dataset
Lecture 4 Face Class 3 : Build ResNet Model
Lecture 5 Face Class 4 : Train Dataset Using ResNet Model
Lecture 6 Face Class 5 : Output & Conclusion
Section 2: Yoga Pose Prediction Project Using ResNet Model
Lecture 7 Introduction To Project
Lecture 8 Yoga Class 1 : Import Packages
Lecture 9 Yoga Class 2 : Import Dataset
Lecture 10 Yoga Class 3 : Dataset Classification
Lecture 11 Yoga Class 4 : Train Dataset Using ResNet Model
Lecture 12 Yoga Class 5 : Output & Conclusion
Section 3: Sign Language Prediction Project Using ResNet Model
Lecture 13 Introduction To Project
Lecture 14 Sign Class 1 : Import Packages
Lecture 15 Sign Class 2 : Import Dataset
Lecture 16 Sign Class 3 : Dataset Classification
Lecture 17 Sign Class 4 : Train Dataset Using ResNet Model
Lecture 18 Sign Class 5 : Output & Conclusion
Section 4: Traffic Sign Prediction Project Using ResNet Model
Lecture 19 Introduction To Project
Lecture 20 Traffic Class 1 : Import Packages
Lecture 21 Traffic Class 2 : Import Dataset
Lecture 22 Traffic Class 3 : Dataset Classification
Lecture 23 Traffic Class 4 : Train Dataset Using ResNet Model
Lecture 24 Traffic Class 5 : Output & Conclusion
Lecture 25 Complete Pnemonia Prediction Project Using ResNet
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