# practicalAI
**Repository Path**: thomas9696/practicalAI
## Basic Information
- **Project Name**: practicalAI
- **Description**: A practical approach to learning machine learning.
- **Primary Language**: Unknown
- **License**: MIT
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No
## Statistics
- **Stars**: 0
- **Forks**: 0
- **Created**: 2020-08-06
- **Last Updated**: 2020-12-19
## Categories & Tags
**Categories**: Uncategorized
**Tags**: None
## README
# PracticalAI
[](https://github.com/GokuMohandas/practicalAI#notebooks)
[](https://github.com/GokuMohandas/practicalAI/blob/master/LICENSE)
Empowering you to use machine learning to get valuable insights from data.
- 🔥 Implement basic ML algorithms and deep neural networks with PyTorch.
- 🖥️ Run everything on the browser without any set up using Google Colab.
- 📦 Learn object-oriented ML to code for products, not just tutorials.
## Notebooks
|Basics|Deep Learning|Advanced|Topics|
|-|-|-|-|
| 📓 [Notebooks](https://colab.research.google.com/github/GokuMohandas/practicalAI/blob/master/notebooks/00_Notebooks.ipynb)|🔥 [PyTorch](https://colab.research.google.com/github/GokuMohandas/practicalAI/blob/master/notebooks/07_PyTorch.ipynb)|📚 [Advanced RNNs](https://colab.research.google.com/github/GokuMohandas/practicalAI/blob/master/notebooks/14_Advanced_RNNs.ipynb)|📸 [Computer Vision](https://colab.research.google.com/github/GokuMohandas/practicalAI/blob/master/notebooks/15_Computer_Vision.ipynb)|
| 🐍 [Python](https://colab.research.google.com/github/GokuMohandas/practicalAI/blob/master/notebooks/01_Python.ipynb)|🎛️ [Multilayer Perceptrons](https://colab.research.google.com/github/GokuMohandas/practicalAI/blob/master/notebooks/08_Multilayer_Perceptron.ipynb)|🏎️ Highway and Residual Networks|⏰ Time Series Analysis|
|🔢 [NumPy](https://colab.research.google.com/github/GokuMohandas/practicalAI/blob/master/notebooks/02_NumPy.ipynb)|🔎 [Data & Models](https://colab.research.google.com/github/GokuMohandas/practicalAI/blob/master/notebooks/09_Data_and_Models.ipynb)|🔮 Autoencoders|🏘️ Topic Modeling|
| 🐼 [Pandas](https://colab.research.google.com/github/GokuMohandas/practicalAI/blob/master/notebooks/03_Pandas.ipynb) |📦 [Object-Oriented ML](https://colab.research.google.com/github/GokuMohandas/practicalAI/blob/master/notebooks/10_Object_Oriented_ML.ipynb)|🎭 Generative Adversarial Networks|🛒 Recommendation Systems|
|📈 [Linear Regression](https://colab.research.google.com/github/GokuMohandas/practicalAI/blob/master/notebooks/04_Linear_Regression.ipynb)|🖼️ [Convolutional Neural Networks](https://colab.research.google.com/github/GokuMohandas/practicalAI/blob/master/notebooks/11_Convolutional_Neural_Networks.ipynb)|🐝 Spatial Transformer Networks|🗣️ Pretrained Language Modeling|
|📊 [Logistic Regression](https://colab.research.google.com/github/GokuMohandas/practicalAI/blob/master/notebooks/05_Logistic_Regression.ipynb)|📝 [Embeddings](https://colab.research.google.com/github/GokuMohandas/practicalAI/blob/master/notebooks/12_Embeddings.ipynb)||🤷 Multitask Learning|
|🌳 [Random Forests](https://colab.research.google.com/github/GokuMohandas/practicalAI/blob/master/notebooks/06_Random_Forests.ipynb)|📗 [Recurrent Neural Networks](https://colab.research.google.com/github/GokuMohandas/practicalAI/blob/master/notebooks/13_Recurrent_Neural_Networks.ipynb)||🎯 Low Shot Learning|
|💥 KMeans Clustering|||🍒 Reinforcement Learning|
## Running the notebooks
1. Access the notebooks in the [`notebooks`](https://github.com/GokuMohandas/practicalAI/tree/master/notebooks) directory in this repo.
2. You can run these notebook on Google Colab (recommended) or on your local machine.
3. Click on a notebook and replace `https://github.com/` with `https://colab.research.google.com/github/` in the notebook URL or use this [Chrome extension](https://chrome.google.com/webstore/detail/open-in-colab/iogfkhleblhcpcekbiedikdehleodpjo) to do it with one click.
4. Sign into your Google account.
5. Click the `COPY TO DRIVE` button on the toolbar. This will open the notebook on a new tab.
5. Rename this new notebook by removing the `Copy of` part in the title.
6. Run the code, make changes, etc. and it's all automatically saved to you personal Google Drive.
## Contributing to notebooks
1. Make your changes and download the Google colab notebook as an .ipynb file.
2. Go to https://github.com/GokuMohandas/practicalAI/tree/master/notebooks
3. Click on `Upload files`.
5. Upload the .ipynb file.
6. Write a detailed commit title and message.
7. Name your branch as appropriately.
8. Click on `Propose changes`.
