If your interested into deep learning for the satellite images, this full hands-on coding workshop is best resources for you. The full workshop is divided into following 3 parts:
1. Data Processing for the Satellite Imagery
- Data Preparation
- Satellite Data Processing
2. Deep Learning with Satellite Image Data
- Deep Learning Model Training
- Local Debugging
- Prediction with model performance
3. Advance Deep Learning with Satellite Image Data
- Remote debugging with Weights & Biases
- Model Saving and Reloading with custom metrics and loss function
- Activation/Gradients outputs with heatmap,
- Model Deployment application and Model Serving app on Hugging Face

GitHub Resources:
- [ Ссылка ]

▬▬▬▬▬▬ ⏰ TUTORIAL TIME STAMPS ⏰ ▬▬▬▬▬▬
- (00:00) Content Starts
- (00:30) What is covered?
- (04:50) Part 1 Refresher
- (06:30) Part 2 Coding Starts
- (09:45) Jaccard Index
- (15:15) U-Net Model Architecture
- (20:01) DL Network Coding Starts
- (36:45) Model Metrics
- (38:20) Code Debugging 1
- (42:45) Custom Loss function
- (49:10) Model Training
- (50:55) Code Debugging 2
- (55:55) Model Metrics/Eval
- (1:02:45) Model Prediction
- (1:02:45) Model Prediction
- (1:10:50) Save/Export Model
- (1:12:30) Model Network Plot
- (1:14:20) Diagnostics with Callback
- (1:27:00) Model Visualization with Netron
- (1:32:00) Source Code at GitHub

Connect
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- Prodramp By Avkash (@prodramp)
- Website - [ Ссылка ]
- LinkedIn - [ Ссылка ]
- GitHub- [ Ссылка ]
- AngelList - [ Ссылка ]
- Facebook - [ Ссылка ]

Content Creator: Avkash Chauhan (@avkashchauhan)
- [ Ссылка ]
- [ Ссылка ]

Tags:
#tensorflow #satelliteimagery #deeplearning #keras #prodramp #avkashchauhan

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