A collection of my machine learning projects as I learn different algorithms.
This model takes input data of how many goals the team will score and predicts the number of points the team will obtain throughout the season. For this I scraped data of goals scored and points obtained from past 5 seasons and implemented a linear regression model from scratch without the use of a library.
This model takes input of total points obtained in season and tries to predict whether that team will finish top 4 and qualify for champions league or not. I collected sample data from past 5 seasons and created a logistic regression model from scratch without the use of library.
This model takes input of over 20 questions to identify covid symptoms and predict the chance of having covid. Dataset was collected from Kaggle.
This model uses the K means clustering algorithm to segment customers based on their spending. This was done on a mall dataset available in Kaggle.
I used the collaborative filtering algorithm to make a recommender system model using the Movie Lens dataset. I implemented the algorithm using Tensorflow according to Andrew Ng's Machine Learning Specialization course.