# 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 [![Colab](https://img.shields.io/badge/launch-Google%20Colab-orange.svg)](https://github.com/GokuMohandas/practicalAI#notebooks) [![MIT](https://img.shields.io/badge/license-MIT-brightgreen.svg)](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`.