Autoplay
Autocomplete
Previous Lesson
Complete and Continue
Deep Learning With Python For Image Classification
Section 1 - Introduction to the Course
Introduction to the Course (2:22)
Section 2 - Define Image Classification
Image Classification with single label and multi-label (2:59)
Section 3 - Pretrained Models Definition
PreTrained Models and their Applications (5:11)
Section 4 - Deep Learning Architectures for Image Classification
Deep Learning ResNet and AlexNet Architectures for Image Classification (4:58)
Section 5 - Google Colab for Writing Python Code
Set-up Google Colab for Writing Python Code (5:11)
Section 6 - Connect Google Colab with Google Drive
Connect Google Colab with Google Drive to Read and Write Data (2:43)
Section 7 - Access Data from Google Drive to Colab
Read Data from Google Drive to Colab Notebook (2:44)
Section 8 - Data Preprocessing for Image Classification
Lecture 1 - Perform Data Preprocessing for Image Classification (5:00)
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
Introduction to Transfer Learning (6:10)
Section 12- Link Google Drive with Google Colab
Link Google Drive with Google Colab (2:43)
Section 13 - Dataset, Data Augmentation, Dataloaders, and Training Function
Dataset, Data Augmentation, Dataloaders, and Training Function (7:20)
Section 14 - Deep ResNet Model FineTuning
Deep ResNet Model FineTuning (7:19)
Section 15 - Model Optimization
ResNet Model HyperParameteres Optimization (6:22)
Section 16 -Deep ResNet Training
Deep ResNet Model Training (3:34)
Section 17 - Deep ResNet Feature Extractor
Deep ResNet as Fixed Feature Extractor (4:42)
Section 18 - Model Optimization, Training and Results
Model Optimization, Training and Results Visualization (5:51)
Section 19 - Resources Code for Transfer Learning by FineTuning and Model Feature Extractor
Code of Classification using Transfer Learning (1:41)
Code for Transfer Learning by FineTuning and Model Feature Extractor
Classification Dataset
Deep Learning ResNet and AlexNet Architectures for Image Classification
Lesson content locked
If you're already enrolled,
you'll need to login
.
Enroll in Course to Unlock