Using Tensorflow to implement basic Deep Learning algorithms
The following information expands on the requirements of Tensorflow_1X_JupyterNotebook
Download the repository and run the codes using:
Python == 3.5
Tensorflow == 1.10.1
| File | Information |
|---|---|
| 1- What are Neural Networks .ipynb | Basics of neural networks |
| 2- Coding a Neural Network from SCRATCH.ipynb | Code an NN from scratch |
| 3- Tensorflow Syntax.ipynb | Basics of TF syntax |
| 4- Tensorflow Graphs.ipynb | Basics of TF graphs |
| 5- Tensorflow Variables and Placeholders.ipynb | Basics of TF placeholders and variables |
| 7- Estimators.ipynb | TF estimators |
| 8- Convolutional Neural Networks.ipynb | CNNs in TF |
The following information expands on the requirements of Tensorflow_2X_JupyterNotebook
Download the repository and run the codes using:
Python == 3.7
Tensorflow == 2+
The notebooks were made using google colab