- Repository containing several mini projects, implementing small scale ML training models using scikit-learn, Keras, TensorFlow, PyTorch. Mainly for fun and learning.
- All instructions are with respect to a terminal in linux/mac. Please use the ubuntu sub-system if you are using windows 10 or use anaconda for windows. A good installation guide for the linux sub-system can be found here
- Folders specific to separate techniques and softwares used.
- Highly recommends installing anaconda to handle the packages and their dependencies.
- Instructions on installation of specific packages in anaconda included in readme.md files.
- All packages are based on python, mostly written in the form of JUPYTER notebooks.
- Many examples taken from Aurélien Géron - Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow_ Concepts, Tools, and Techniques to Build Intelligent Systems (2019, O’Reilly Media) and other relevant books on practical machine learning.
- Separate readme files might be added to folders, whereever deemed necessary.
Manu Jayadharan, Department of Mathematics at University of Pittsburgh, 2020
email: manu.jayadharan@gmail.com, manu.jayadharan@pitt.edu
researchgate
linkedin
- A good documentation on installatin of anaconda can be found here.
- Creating an environment in anaconda to keep the package versions consistent:
conda create --name myenv
conda activate myenv
- Installing jupyter notebook:
conda install jupyter
- Starting a jupyter notebook:
jupyter notebook