Welcome to my GitHub profile! I am a dedicated Data Science enthusiast with a good background in Python, R, and various data analysis and machine learning libraries. My passion lies in turning data into actionable insights and developing robust models that solve real-world problems.
I have a great interest in data science and machine learning, with some experience in:
- Data Analysis: Experienced in Extracting, cleaning, and transforming data using Pandas and Polars.
- Machine Learning: Proficient in Building predictive models with scikit-learn.
- Deep Learning: Familiar with Developing neural networks and models using PyTorch and TensorFlow (Mostly Dense and CNN).
- Statistical Analysis: Familiar with statistical analysis and hypothesis testing using R.
- Optimization: Familiar with Solving optimization problems with CVXPY.
- Async Programming: asynchronous code execution using AsyncIO in order to gather data from APIs.
- Web Scraping and API Interaction: Utilizing Requests for web data retrieval.
- Boosting Algorithms: Implementing high-performance models using XGBoost and LightGBM.
- Database Management: querying relational databases using MySQL (HackerRank Certificate).
- Data Visualization: Creating visualizations using Matplotlib and Plotly.
- NLP
- Deep Learning
- Transformers
- Financial Markets prediction
- Time series segmentation algorithms (Change point detection analysis)
- Autoencoders (using CNN neural nets)
- Fetching live data using async requests from stock website.
- Learn-To-Rank algortihms (DeepRank, LambdaMart)
- Bayesian Portfoilio analysis
- Hidden Markov Models (To detect different states in time series)
- Detecting Motifs (using
stumpypackage)
- Python (Familiar with Functional and OOP Programming)
- R
- My SQL
- Pandas
- Polars
- scikit-learn
- PyTorch
- TensorFlow
- XGBoost
- LightGBM
- AsyncIO
- Requests
- CVXPY
- Jupyter Notebook/VS Code
- RStudio
- Git & GitHub
- CodeSpaces
Feel free to connect with me on LinkedIn:
Thank you for visiting my profile. Happy coding! 😊