ML_mini_projects using anaconda

• 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.

Author

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Manu Jayadharan, Department of Mathematics at University of Pittsburgh, 2020

email: manu.jayadharan@gmail.com, manu.jayadharan@pitt.edu
researchgate
linkedin

Installing anaconda

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• 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