Repository for Data Analysis and Machine Learning source code. The code in this repository is divided into 2 types:
This is for the basics of Data Analysis and Machine Learning techniques, the source code for these techniques are writtent from Scratch (No Scikit/Keras used).
This repository also contains applications of these techniques, most of them are in the field of sports, over here you can find some of the uses of the code that we implemented above. The application code uses Scikit-Learn and FBProphet in certain cases for demonstration.
This directory contains source code for different types of Neural Networks. This includes, single-layered networks, multi-layered networks, as well as networks with different non-linearities (Sigmoid, Tanh etc.). All of these modules are made from scratch (No Scikit/Keras used)
More specific information of this directory can be found in its README.
The code in this directory contains the implementation of different Unsupervised Learning techniques in Python from scartch (No external ML libraries used).
More specific information of this directory can be found in its README.
The code in this directory will contain the Python source code for visualizing and infering from data from different types of Probability distributions. More specific information can be found within this directory.
The Python Libraries used in this repository are:
- Basic Libraries like Numpy and Pandas
- Dash (for creating plots)
- Scikit-learn
- FBProphet
For any concerns, suggestions, queries or something else, please contact me at:
rohan.b.singh54@gmail.com
rxs1182@case.edu