[NEW] 2024:Build 15+ Real-Time Computer Vision Projects

CNN,GAN,Transfer Learning, Data Augmentation/Annotation, Deepfake, YOLO ,Face recognition,object detection,tracking

Ratings: 4.53 / 5.00




Description

Build 15+ Real-Time Deep Learning(Computer Vision) Projects


Ready 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:


Project 6: Master object detection with the powerful YOLOv5 model.

Project 7: Leverage the cutting-edge YOLOv8-cls for image and video classification.

Project 8: Delve into instance segmentation using YOLOv8-seg to separate individual objects.

Mini Project 1: Explore YOLOv8-pose for keypoint detection.

Mini Project 2 & 3: Make real-time predictions on videos and track objects using YOLO.

Project 9: Build a system for object tracking and counting.

Mini Project 4: Utilize the YOLO-WORLD Detect Anything Model for broader object identification.


Image Analysis & Beyond:


Project 1 & 2: Get started with image classification on classic datasets like MNIST and Fashion MNIST.

Project 3: Master Keras preprocessing layers for image manipulation tasks like translations.

Project 4: Unlock the power of transfer learning for tackling complex image classification problems.

Project 5: Explore the fascinating world of image captioning using Generative Adversarial Networks (GANs).

Project 10: Train models to recognize human actions in videos.

Project 11: Uncover the secrets of faces with face detection, recognition, and analysis of age, gender, and mood.

Project 12: Explore the world of deepfakes and understand their applications.

Mini Project 5: Analyze images with the pre-trained MoonDream1 model.


Why Choose This Course?


Learn by Doing: Each project provides practical coding experience, solidifying your understanding.

Cutting-edge Tools: Master the latest advancements in Computer Vision with frameworks like YOLOv5 and YOLOv8.

Diverse Applications: Gain exposure to various real-world use cases, from object detection to deepfakes.

Structured Learning: Progress through projects with clear instructions and guidance.


Ready to take your Computer Vision skills to the next level? Enroll now and start building your portfolio!



Core Concepts:


    Image Processing: Pixel manipulation, filtering, edge detection, feature extraction.

    Machine Learning: Supervised learning, unsupervised learning, deep learning (specifically convolutional neural networks - CNNs).

    Pattern Recognition: Object detection, classification, segmentation.

    Computer Vision Applications: Robotics, autonomous vehicles, medical imaging, facial recognition, security systems.


Specific Terminology:


Object Recognition: Identifying and classifying objects within an image.

    Semantic Segmentation: Labeling each pixel in an image according to its corresponding object class.

    Instance Segmentation: Identifying and distinguishing individual objects of the same class.


Technical Skills:


    Programming Languages: Python (with libraries like OpenCV, TensorFlow, PyTorch).

    Hardware: High-performance computing systems (GPUs) for deep learning tasks.


Additionally:


    Acronyms:  YOLO, R-CNN (common algorithms used in computer vision).

    Datasets: ImageNet, COCO (standard datasets for training and evaluating computer vision models).

What You Will 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

Who Should Attend!

  • 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