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

Requirements

A Google Gmail account is required to get started with Google Colab to write Python Code

Python Programming experience is an advantage but not required