Deep Learning and Neural Networks with Python Zero to Expert

سرفصل های دوره

Deep Learning with Python for Classification, Semantic and Instance Segmentation, Pose Estimation, and Object Detection

1. Introduction

1. Introduction

2. Introduction to Deep Learning

1. Introduction to Deep Learning vs Machine Learning

2. Building Blocks of Deep Learning - Artificial Neurons

3. Artificial Neural Networks with Python

1. Introduction to Neural Networks.html

2. Perceptron -- Building Block of Neural Networks.html

3. Colab for Writing Python Code

4. Convolutional Neural Networks with Python from Scratch

1. Introduction to Convolutional Neural Networks (CNNs)

2. Coding Convolutional Neural Networks from Scratch with Python

3. Develop CNN with Python and Pytroch Code from Scratch.html

4. Dataset and its Augmentation

5. Pytorch Code for Data Loading and Augmentation.html

6. Hyperparameters Optimization For Convolutional Neural Networks

7. CNN Optimization with Pytorch and Python Code.html

8. Training Convolutional Neural Network from Scratch

9. CNN Training with Python and Pytorch Code.html

10. Validating Convolutional Neural Network on Test Images

11. CNN Testing with Pytorch and Python Code.html

12. Performance Metrics (Accuracy, Precision, Recall, F1 Score) to Evaluate CNNs

13. Visualize Confusion Matrix and Calculate Precision, Recall, and F1 Score

14. Performance Metrics Calculation with Python and Pytorch Code.html

15.1 CNN from Scratch Code.zip

15. Resources Python Code for Convolutional Neural Networks from Scratch.html

5. Deep Convolutional Neural Networks with Python for Image Classification

1. Coding DEEP CNN from Scratch for Image Classification

2. Optimize, Train and Test Deep CNN with Improved Performance

3. Deep CNN Python and Pytroch Code.html

6. Deep Learning Pretrained Models with Python

1. PreTrained Deep Learning Models Importance

2. Deep Learning ResNet and AlexNet Architectures

3. Read Data from Google Drive to Colab Notebook

4. Perform Data Preprocessing

5. Use ResNet and AlexNet PreTrained Models

6.1 imagenet1000Classes.txt

6.2 pizza.zip

6.3 single-label classification.zip

6. Python Code for Pretrained ResNet and AlexNet.html

7. Transfer Learning with Python

1. Why Transfer Learning

2. Data Augmentation, Dataloaders, and Training Function

3. FineTuning Deep ResNet Model

4. Optimization of ResNet Model HyperParameteres

5. Deep ResNet Model Training

6. Deep ResNet Model as Fixed Feature Extractor

7. Results and Training of Model as Fixed Feature Extractor

8. Deep Learning for Object Detection on Custom Dataset

1. Introduction to Object Detection

2. Overview of CNN, RCNN, Fast RCNN, and Faster RCNN

3. Detectron2 for Ojbect Detection with PyTorch

4. Perform Object Detection using Detectron2 Pretrained Models

5.1 Python and PyTorch Code for Object Detection using Detectron2.zip

5. Python and PyTorch Code for Object Detection using Detectron2.html

6. Custom Dataset for Object Detection

7.1 Balloon Dataset.zip

7. Balloon Dataset.html

8. Train, Evaluate Object Detection Models & Visualizing Results on Custom Dataset

9.1 Python and Pytroch Code for Object Detection On Custom Dataset.zip

9. Python and Pytroch Code for Object Detection On Custom Dataset.html

9. Deep Learning for Video Object Detection

1. What is YOLO

2. How YOLO works for Object Detection

3. YOLOv8 Introduction and Architecture

4. Custom Vehicles Detection Dataset

5. HyperParameters Settings for YOLO8

6. Training YOLO8 on Vehicles Dataset

7. Testing YOLO8 on Videos and Images

8. Calculate Performance Metrics (Precision, Recall, Mean Average Precision mAP)

9. Deploy YOLO8

10.1 TestVideo.zip

10.2 VehiclesDetection Dataset.zip

10.3 vehiclesdetectioncode.zip

10. Resources Videos Vehicles Detection Complete Code and Dataset.html

10. Deep Learning for Pose Estimation with Python

1. Introduction to Pose Estimation.html

2. Pose Estimation and Key Points Detection with Python.html

11. Deep Learning for Instance Segmentation

1. What is Instance Segmentation

2. Deep Learning Architecture Mask RCNN for Instance Segmentation

3. Instance Segmentation PyTorch Facebook Library

4. Custom Dataset for Instance Segmentation

5. Train, Evaluate & Visualize Instance Segmentation on Custom Dataset

6.1 Balloon Dataset.zip

6.2 Python and Pytorch Code of Instance Segmentation on Custom Dataset.zip

6. Resources Code and Dataset for Instance Segmentation.html

12. Deep Learning for Semantic Segmentation

1. Introduction to Semantic Segmentation

2. Semantic Segmentation Real-world Applications

3. Pyramid Scene Parsing Network for Segmentation

4. UNet Architecture for Segmentation

5. Pyramid Attention Network for Segmentation

6. Multi-Task Contextual Network for Segmentation

7. Datasets for Semantic Segmentation

8. Data Annotations Tool for Semantic Segmentation

9.1 TrayDataset for Segmentation.zip

9. Dataset for Semantic Segmentation.html

10. Data Loading with PyTorch Customized Dataset Class

11. Data Augmentation using Albumentations with different Transformations

12. Data Loaders Implementation in Pytorch

13. Performance Metrics (IOU, Pixel Accuracy) for Segmentation Models Evaluation

14. Learn Transfer Learning with Deep Resnet Architecture

15. Encoders for Segmentation in PyTorch

16. Decoders for Segmentation in PyTorch

17. Implement Segmentation Models (UNet, PSPNet, DeepLab, PAN, UNet++)

18. Hyperparameters Optimization of Segmentation Models

19. Training of Segmentation Models

20. Test & Deploy Segmentation Models and Calculate Class-wise IOU, Accuracy, Fscore

21. Visualize Segmentation Results and Generate RGB Output Segmentation Map

22.1 Final Code.zip

22.2 TrayDataset for Segmentation.zip

22. Resources Code and Dataset of Segmentation with Deep Learning.html

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تولید کننده: Udemy