Python
Skills for certificate:
Flask
Django
Gunicorn
Jinja
Simple GUI
SQLAlchemy
Symphony BDK
Black
PyLint
PyTest
UnitTest
Poetry
Pip
PyBuilder
Scikit Learn
TensorFlow
PyTorch
Pandas
NumPy
Matplotlib
Seaborn
Jupyter Notebooks
Keras
Machine Learning
Deep Learning
Artificial Intelligence
Data Science
Hyperparameters
Boosting
Data Visualisation
Neural Networks
Web Development
Python
This is the page displaying all the material related to Python. This can include projects, blogs, certificates, university modules and work experience along with sub-skills.
Material
Flask Forum Backend
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.
Flask Backend Demo
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.
Flask JWT Authentication
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.
Django Authentication
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.
Handwritten Digit Classifier
A handwritten digit classifier using built using a Convolutional Neural Network (CNN). Used various techniques such as data augmentation, batch normalisation, and dropout to improve the model's performance.
Adult Income Prediction
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.
House Price Prediction
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.
Pacman Neural Network Classifier
Built a neural network from scratch to detect Pacman's direction in the game. Used various techniques such as batch normalisation, dropout, momentum, learning rate decay and more to improve the model's performance.
Machine Learning Algorithms
Practicing various algorithms and techniques. This includes supervised, unsupervised, and reinforcement learning algorithms, as well as feature engineering, data preprocessing, and hyperparameter tuning.
Reinforcement Learning Lab
Practicing various Reinforcement Learning algorithms and techniques. This includes Q-Learning, Deep Q-Learning, and Asynchronous Advantage Actor-Critic (A3C) algorithms.
Machine Learning Assignment 1
Implementing algorithms from scratch such as the Nearest Neighbours algorithm. Requires an understanding of the Mathematics behind the algorithms and the ability to implement them.
Machine Learning Assignment 2
Be able to use and implement algorithms, with the Lasso and inductive conformal prediction algorithms as examples.
Machine Learning Assignment 3
Be able to use and implement algorithms, with the SVM, neural networks, and cross-conformal prediction algorithms as examples.
Machine Learning Labs
Implemented various algorithms and techniques learnt during the course, such as Nearest Neighbours, Conformal Prediction, Regression algorithms, data preprocessing, kernels, Neural Networks, SVMs, etc.
Computational Finance Assignment
Exploring valuation of options using methods like Black-Scholes, binomial trees, and Monte Carlo. Also includes theoretical aspects of put-call parity and financial arbitrage opportunities.
Machine Learning & Data Science Lab
Focusing on learning generative models, using third-party models and using advanced techniques. This includes techniques such as transfer learning, LLM Agents, and Generative Models.
Pacman Game
Pacman agent plays to win the game while handling stochasticity in the movement of agent and ghosts. Uses Markov Decision Processes, Value Iteration and other enhancements.
Leetcode Solutions
A collection of Leetcode solutions in Python. This is used to practice algorithms and data structures. They are also used to practice unit testing. CI/CD is also used to run the tests when merging to the main branch.
Searching & Sorting Algorithms
Jupyter Notebook containing various searching and sorting algorithms. Each algorithms is explained. All the algorithms are also compared to each other.
Osmos Game
A simple game built with SimpleGUI for a first-year university project. We manually implemented physics using vector theory and physics concepts, relying solely on documentation due to the lack of tutorials.