This is a custom backend for the first iteration of the discussion platform. This was created to learn how to create a custom backend using Python and Flask.

A simple Flask app to learn how to create a RESTful API. This was a foundational project to learn how to create a back-end using Flask. This was helpful when creating the back-end for the discussion platform.

A simple Flask app to learn how to use JWT for authentication. This serves as a foundation to using JWT in other projects using Flask.

A simple Django app to learn how to use Django with tokens for authentication. This serves as a foundation to using Django in other projects.

A project comparing various classification algorithms to predict whether an adult earns more than $50,000 a year. Emphasis is on feature engineering, data preprocessing with One-Hot Encoding, and model optimization through hyperparameter tuning.

A project comparing various regression algorithms to predict house prices in relation to the distance from the coast. Emphasis is on feature engineering, data preprocessing with One-Hot Encoding, and model optimization through hyperparameter tuning.

Practicing various Machine Learning algorithms and techniques. This includes supervised, unsupervised, and reinforcement learning algorithms, as well as feature engineering, data preprocessing, and hyperparameter tuning. Some additional content in the field of Deep Learning and Neural Networks are also covered.

Practicing various Reinforcement Learning algorithms and techniques. This includes Q-Learning, Deep Q-Learning, and Asynchronous Advantage Actor-Critic (A3C) algorithms.

Jupyter Notebook containing various searching and sorting algorithms. Each algorithms is explained. All the algorithms are also compared to each other.