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 stumpy package)

• 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! 😊