Deep Learning : Convolutional Neural Networks With Python

What you’ll learn

• Deep Convolutional Neural Networks with Python and Pytorch Basics to Expert
• Introduction to Deep Learning and its Building Blocks Artificial Neurons
• Define Convolutional Neural Network Architecture from Scratch with Python and Pytorch
• Hyperparameters Optimization For Convolutional Neural Networks to Improve Model Performance
• Custom Datasets with Augmentations to Increase Image Data Variability
• Training and Testing Convolutional Neural Network using Pytorch
• Performance Metrics (Accuracy, Precision, Recall, F1 Score) to Evaluate CNNs
• Visualize Confusion Matrix and Calculate Precision, Recall, and F1 Score
• Advanced CNNs for Segmentation, Object tracking, and Pose Estimation.
• Pretrained Convolutional Neural Networks and their Applications
• Transfer Learning using Convolutional Neural Networks Models
• Convolutional Neural Networks Encoder Decoder Architectures
• YOLO Convolutional Neural Networks for Computer Vision Tasks
• Region-based Convolutional Neural Networks for Object Detection