Model Optimization, Training and Results Visualization

Deep Learning With Python For Image Classification

Section 1 - Introduction to the Course

Section 2 - Define Image Classification

Section 3 - Pretrained Models Definition

Section 4 - Deep Learning Architectures for Image Classification

Section 5 - Google Colab for Writing Python Code

Section 6 - Connect Google Colab with Google Drive

Section 7 - Access Data from Google Drive to Colab

Section 8 - Data Preprocessing for Image Classification

Section 9 - Single-Label Image Classification using Deep Learning Models

Single-Label Image Classification using ResNet and AlexNet PreTrained Models (8:03)
Resources Single_Label Classification (Python Code)

Section 10 - Multi-Label Image Classification using Deep Learning Models

Lecture 2 - Resources Multi_Label Classification
Multi-Label Image Classification using ResNet and AlexNet PreTrained Models (6:21)

Section 11- Transfer Learning

Section 12- Link Google Drive with Google Colab

Section 13 - Dataset, Data Augmentation, Dataloaders, and Training Function

Section 14 - Deep ResNet Model FineTuning

Section 15 - Model Optimization

Section 16 -Deep ResNet Training

Section 17 - Deep ResNet Feature Extractor

Section 18 - Model Optimization, Training and Results

Section 19 - Resources Code for Transfer Learning by FineTuning and Model Feature Extractor

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