This is my implementation of the class assignments of the Specialization teached by Laurence Moroney. I add some modifies and other reading materials in addition to the old labs and assignments. In each Course directory, I also put the slides in it for other to reference. More information can be found in this course's website and Deepleaning.ai community.
By the way, I want to notice who want to learn this course that you may need to go to another basic course. This is also teached by Laurence and covers some basic knowledge you must know before stepping into this Advanced Techniques Specialization.
Deeplearning.AI TensorFlow: Advanced Techniques Specialization Solution
| Sr | Weeks | Link |
|---|---|---|
| 1 | Functional API | Link |
| 2 | Custom Loss Functions | Link |
| 3 | Custom Layers | Link |
| 4 | Custom Models, Layers, and Loss Functions with Tensorflow | Link |
| Sr | Weeks | Link |
|---|---|---|
| 1 | Differentiation and Gradients | Link |
| 2 | Custom Training | Link |
| 3 | Graph Mode | Link |
| 4 | Custom and Distribnuted Training with Tensorflow | Link |
| Sr | Weeks | Link |
|---|---|---|
| 1 | Introduction to Computer Vision | Link |
| 2 | Object Detection | Link |
| 3 | Image Segmentation | Link |
| 4 | Visualization and Interpretability | Link |
| Sr | Weeks | Link |
|---|---|---|
| 1 | Style Transfer | Link |
| 2 | AutoEncoders | Link |
| 3 | Variance AutoEncoders | Link |
| 4 | GANS | Link |