Stock Market Analysis using basic Machine Learning

  • Machine Learning

  • Image Processing

Mentors :

  • Prashul Vaishnav

  • Goransh Gattani

Mentees :

  • 4

Get to know the basics of python and its libraries, and learn how to apply them on real life data of Stock Market

Tentative Timeline :

Week Number Tasks to be Completed
Week 1 Python basics like loop, variables, funcitons, lists, tuples
Week 2 Git, google colab, python libraries like numpy, pandas, matplotlib
Week 3 ML basics - supervised learning part 1 : linear regression, gradient descent, loss function, SVMs
Week 4 ML basics- supervised learning part 2: logistic regression, sgd, regularisation, bias/variance
Week 5 ML basics- unsupervised learning part 1: KMeans clustering, Hyperparameter tuning,
Week 6 ML basics - unsupervised learning part 2: Metrics, error analysis, Classification metrics, regression metrics.
Week 7 Stock market: implementation of the learnt concept in the project, implementation like, preprocessing and applying models