Hands on Machine Learning Workbooks

This is a repo in which I will have multiple notebooks explaining topics of ML
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Table of Contents

1. About The Project
   • Built With
2. Getting Started
   • Prerequisites
   • Installation
3. Usage
4. Roadmap
5. License
6. Contact

About The Project

This repo houses multiple practice tutorials built around books I have been reading and things I've faced in my career.

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Built With

• Python
• Anaconda
• Scikit-Learn
• Pandas
• TensorFlow
• Hugginface Transformers

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Getting Started

I recommend creating a virtual environment using anaconda with all required dependencies to run these notebooks

Prerequisites

This is an example of how to list things you need to use the software and how to install them.

• environment generation

  conda install -n your_environment_name python=3.8
  conda activate your_environment_name
  pip install requirements.txt
  

Usage

1. Clone the repo

   git clone https://github.com/rod08018/Hands-on-ML.git

2. run jupyter notebook

    jupyter notebook
   

3. Open specific notebook in the browser to start testing code

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Roadmap

• Simple Regression
• Binary Classification
• Multiclass Classification
• Linear Regression
• Gradient Descent
• Non-Linear Regression
• Learning Curves
• Regularized Linear Models
  • Ridge
  • Lasso
  • Elastic Net
  • Early Stopping
• Logistic Regression
• Support Vector Machines
• Decision Trees
• Ensemble Learning and Random Forests
• Dimensionality Reduction
  • PCA
  • Kernel PCA
• Unsupervised Learning Techniques
• Neural Networks and Deep Learning with Keras
• RNN and CNNs
• NLP with RNNs and Attention
• Representation Learning and Generative Learning using Autoencoders and GANs
• Reinforcement Learning

See the open issues for a full list of proposed features (and known issues).

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Contributing

Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.

If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement". Don't forget to give the project a star! Thanks again!

1. Fork the Project
2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
3. Commit your Changes (git commit -m 'Add some AmazingFeature')
4. Push to the Branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

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License

Distributed under the MIT License. See LICENSE.txt for more information.

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Contact

Jose Rodriguez - Linkedin

Project Link: https://github.com/rod08018/Hands-on-ML

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