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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Machine learning notebooks in different subjects optimized to run in google collaboratory
| Date | Stars |
|---|---|
| 2026-07-31 | 372 |
| 2026-08-06 | 372 |
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# Notebooks
<table class="tg">
<tr>
<th class="tg-yw4l"><b>Name</b></th>
<th class="tg-yw4l"><b>Description</b></th>
<th class="tg-yw4l"><b>Category</b></th>
<th class="tg-yw4l"><b> Link </b></th>
</tr>
<tr>
<td class="tg-yw4l">Training pix2pix</td>
<td class="tg-yw4l">This notebook shows a simple pipeline for training pix2pix on a simple dataset. Most of the code is based on <a href = 'https://github.com/affinelayer/pix2pix-tensorflow' >this implementation</a>. </td>
<td class="tg-yw4l">GAN</td>
<td class="tg-yw4l"><a href="https://colab.research.google.com/github/zaidalyafeai/Notebooks/blob/master/tf_pix2pix.ipynb">
<img src="https://colab.research.google.com/assets/colab-badge.svg" width = '800px' >
</a></td>
</tr>
<tr>
<td class="tg-yw4l">One Place</td>
<td class="tg-yw4l">This notebook shows how to train, test then deploy models in the browser directly from one notebook. We use a simple XOR example to prove this simple concept.</td>
<td class="tg-yw4l">Deployment</td>
<td class="tg-yw4l"><a href="https://colab.research.google.com/github/zaidalyafeai/Notebooks/blob/master/ONePlace.ipynb">
<img src="https://colab.research.google.com/assets/colab-badge.svg" >
</a></td>
</tr>
<tr>
<td class="tg-yw4l">TPU vs GPU</td>
<td class="tg-yw4l">Google recently allowed training on TPUs for free on colab. This notebook explains how to enable TPU training. Also, it reports some benchmarks using mnist dataset by comparing TPU and GPU performance.</td>
<td class="tg-yw4l">TPU</td>
<td class="tg-yw4l"><a href="https://colab.research.google.com/github/zaidalyafeai/Notebooks/blob/master/GPUvsTPU.ipynb">
<img src="https://colab.research.google.com/assets/colab-badge.svg" >
</a></td>
</tr>
<tr>
<td class="tg-yw4l">Keras Custom Data Generator</td>
<td class="tg-yw4l">This notebook shows to create a custom data genertor in keras.</td>
<td class="tg-yw4l">Data Generatation</td>
<td class="tg-yw4l"><a href="https://colab.research.google.com/github/zaidalyafeai/Notebooks/blob/master/Custom_Data_Generator_in_Keras.ipynb">
<img src="https://colab.research.google.com/assets/colab-badge.svg" >
</a></td>
</tr>
<tr>
<td class="tg-yw4l">Eager Execution (1)</td>
<td class="tg-yw4l">As we know that TenosrFlow works with static graphs. So, first you have to create the graph then execute it later. This makes debugging a bit complicated. With Eager Execution you can now evalute operations directly without creating a session. </td>
<td class="tg-yw4l">Dynamic Graphs </td>
<td class="tg-yw4l"><a href="https://colab.research.google.com/github/zaidalyafeai/Notebooks/blob/master/Eager_Execution_Gradient_.ipynb">
<img src="https://colab.research.google.com/assets/colab-badge.svg" >
</a></td>
</tr>
<tr>
<td class="tg-yw4l">Eager Execution (2)</td>
<td class="tg-yw4l">In this notebook I explain different concepts in eager execution. I go over variables, ops, gradients, custom gradients, callbacks, metrics and creating models with tf.keras and saving/restoring them.</td>
<td class="tg-yw4l">Dynamic Graphs </td>
<td class="tg-yw4l"><a href="https://colab.research.google.com/github/zaidalyafeai/Notebooks/blob/master/Eager_Execution_Enabled.ipynb">
<img src="https://colab.research.google.com/assets/colab-badge.svg" >
</a></td>
</tr>
<tr>
<td class="tg-yw4l">Sketcher</td>
<td class="tg-yw4l">Create a simple app to recognize 100 drawings from the quickdraw dataset. A simple CNN model is created and served to deoploy in the browser to create a sketch recognizer app. </td>
<td class="tg-yw4l"> Deployment </td>
<td class="tg-yw4l"><a href="https://colab.research.google.com/github/zaidalyafeai/Notebooks/blob/master/Sketcher.ipynb">
<img src="https://colab.research.google.com/assets/colab-badge.svg" >
</a></td>
</tr>
<tr>
<td class="tg-yw4l">QuickDraw10</td>
<td class="tg-yw4Excerpt of 12,987 characters
Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:93bb93ffe62ee4b1, llm:description: 'Machine learning notebooks in different subjects optimized to run in google collaboratory'
matched fp:93bb93ffe62ee4b1, llm:description: 'Machine learning notebooks in different subjects optimized to run in google collaboratory'