Free Download Build 15+ Real-Time Deep Learning(Computer Vision) Projects
Published 3/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 5.84 GB | Duration: 9h 45m
CNN,GAN,Transfer Learning, Data Augmentation/Annotation, Deepfake, YOLO ,Face recognition,object detection,tracking
What you'll learn
DEEP LEARNING
PROJECTS
COMPUTER VISION
YOLOV8
YOLO
DEEPFAKE
OBJECT RECOGNITION
OBJECT TRACKING
INSTANCE SEGMENTATION
IMAGE CLASSIFICATION
IMAGE ANNOTATION
HUMAN ACTION RECOGNITION
FACE RECOGNITION
FACE ANALYSIS
IMAGE CAPTIONING
POSE DETECTION/ACTION RECOGNITION
KEYPOINT DETECTION
SEMANTIC SEGMENTATION
Image Processing
Pixel manipulation
edge detection
feature extraction
Machine Learning
Pattern Recognition
Object detection
classification
segmentation
Python
TensorFlow
PyTorch
R-CNN
ImageNet
COCO
Requirements
MACHINE LEARNING Basics
Python Developers with basic ML knowledge
Python
Description
Build 15+ Real-Time Deep Learning(Computer Vision) ProjectsReady to transform raw data into actionable insights?This project-driven Computer Vision Bootcamp equips you with the practical skills to tackle real-world challenges.Forget theory, get coding!Through 12 core projects and 5 mini-projects, you'll gain mastery by actively building applications in high-demand areas:Object Detection & Tracking
Overview
Section 1: Project 1. Image Classification MNIST Dataset
Lecture 1 Problem : Image Classification MNIST Dataset
Lecture 2 Solution : Image Classification MNIST Dataset
Section 2: Project 2. Image Classification on Fashion MNIST Dataset
Lecture 3 Problem :Image Classification on Fashion MNIST Dataset
Lecture 4 Solution :Image Classification on Fashion MNIST Dataset
Section 3: Project 3. Using Keras Preprocessing Layers for image translations.
Lecture 5 Problem : Using Keras Preprocessing Layers for image translations.
Lecture 6 Solution : Using Keras Preprocessing Layers for image translations.
Section 4: Project 4. Transfer Learning for Image classification on complex dataset
Lecture 7 Problem :Transfer Learning for Image classification on complex dataset
Lecture 8 Solution :Transfer Learning for Image classification on complex dataset
Section 5: Project 5. Image Captioning using GANs
Lecture 9 Problem : Image Captioning using GANs
Lecture 10 Solution : Image Captioning using GANs Part1
Lecture 11 Solution : Image Captioning using GANs Part2
Lecture 12 Solution : Image Captioning using GANs Part3
Section 6: Annotation Tools
Lecture 13 Annotation Tools
Section 7: Project 6. Object Detection using YOLOv5 Model
Lecture 14 Problem : Object Detection using YOLOv5 Model
Lecture 15 Solution : Object Detection using YOLOv5 Model
Section 8: Project 7. Image / video classification using YOLOV8-cls
Lecture 16 Problem : Image / video classification using YOLOV8-cls
Lecture 17 Solution : Image / video classification using YOLOV8-cls
Section 9: Project 8. Instance Segmentation using YOLOV8-seg
Lecture 18 Problem : Instance Segmentation using YOLOV8-seg
Lecture 19 Solution : Instance Segmentation using YOLOV8-seg
Section 10: Mini Project 1 :Yolov8-Pose Keypoint Detection
Lecture 20 Problem :Yolov8-Pose Keypoint Detection
Lecture 21 Solution :Yolov8-Pose Keypoint Detection
Section 11: Mini Project 2: Predictions on Videos using YOLOV8
Lecture 22 Problem
Lecture 23 Solution
Section 12: Mini Project 3: Object Tracking using YOLO
Lecture 24 Problem :Object Tracking using YOLO
Lecture 25 Solution :Object Tracking using YOLO
Section 13: Project 9. Object Tracking and Counting
Lecture 26 Problem :Object Tracking and Counting
Lecture 27 Solution :Object Tracking and Counting
Section 14: Mini Project 4: YOLO-WORLD Detect Anything Model
Lecture 28 Problem : YOLO-WORLD Detect Anything Model
Lecture 29 Solution : YOLO-WORLD Detect Anything Model
Section 15: Mini Project 5 MoonDream1 Image Analysis
Lecture 30 Problem : MoonDream1 Image Analysis
Lecture 31 Solution : MoonDream1 Image Analysis
Section 16: Project 10. Human Action Recognition
Lecture 32 Problem : Human Action Recognition
Lecture 33 Solution : Human Action Recognition
Section 17: Project 11. Face Detection & Recognition (AGE GENDER MOOD Analysis)
Lecture 34 Problem : Face Detection & Recognition
Lecture 35 Solution : Face Detection & Recognition
Section 18: Project 12. Deepfake Generation
Lecture 36 Problem : Deepfake Generation
Lecture 37 Solution : Deepfake Generation
Beginner ML practitioners eager to learn Deep Learning,Anyone who wants to learn about deep learning based computer vision algorithms,Python Developers with basic ML knowledge
Homepage
Code:
Bitte
Anmelden
oder
Registrieren
um Code Inhalt zu sehen!
Recommend Download Link Hight Speed | Please Say Thanks Keep Topic Live
Code:
Bitte
Anmelden
oder
Registrieren
um Code Inhalt zu sehen!