My first Machine Learning project!! I implemented some basic algorithms like Batch Gradient Descent, Stochastic Gradient Descent, Polynomial Regression using L1 and L2 Regularization from scratch. I used numpy to create my own dataset based on a known function(eg. y = x1 + x2 for gradient descent). This was the first time I used object oriented programming in Python for an actual project. I gained an insight into hyper-parameter tuning and the importance of scaling the input. After this project I was able to truly appreciate the math behind these algorithms. It was a lot of fun plotting the results of my model and even comparing the results with popular libraries.
This is a native android application made using Android Studio and Java for renting houses and putting houses up for rent. This was the first time I made an android application with Firebase. The application includes features such as adding a new property for rent, requesting a property for renting, managing rent requests for properties owned by a user. This project made me comfortable working with Firebase Auth, Firebase Realtime Database, working with recycler views in Android Studio and making custom adapters for them, card views and NoSQL. It was interesting to think about how to tackle multiple users trying to rent the same property at the same time.
