💫 About Me:

Hi! I'm a Software Engineer specializing in data-driven solutions and automation. Currently, I'm developing a Job Application program integrating with LinkedIn, Zip Recruiter, Indeed, and Glassdoor, using Python, SQL, and Excel. I'm also exploring Langchain LLMs for automated Cover Letters, Resumes, and email analysis. I'm open to collaborating on Data Analyst projects, LLM projects, SQL, Excel, Tableau, and POWERBI. Seeking assistance with troubleshooting complex datasets in financial and environmental economics. Currently learning LLM API integrations, advanced Data Analysis, and gaining proficiency in POWERBI and Tableau. Ask me about Docker, Python, or trading algorithm development

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Teoman Selcuk 's Projects

chatgpt-research

The objective of this project is to see how well chatGPT can answer various math questions that are simplistic and cognitively demanding

hummingbot

Hummingbot is open source software that helps you build trading bots that run on any exchange or blockchain

langchain-workflows

LangChain Workflows is a Python-based project that leverages advanced language models to generate concise workflow prompts from input text. It provides a streamlined process from reading and processing input to generating and saving workflow prompts, making it a powerful tool for text analysis and information extraction.

lisp-sbcl-slime-emacs

Docker environment sets up an Ubuntu-based container with a non-root user, installs the required packages, configures sudo, clones your Emacs configuration, installs Roswell, and sets up environment variables.

md-note-taker-mdbook

python code that turns notes and highlights into new reformatted md files.

mth-500

This setup enables you to experiment with stochastic processes and probability concepts using Jupyter Notebook in a containerized environment, making it easy to manage and share your work.

portfolio-benchmarks

This project aims to analyze and visualize the performance of a stock portfolio alongside market indices such as the S&P 500 and TSX300. It utilizes various Python libraries including pandas, numpy, plotly, and scikit-learn for data manipulation, visualization, and predictive modeling.

pptx-to-rts-converter

convert PowerPoint files to RTS files

r-housing-price-predictions

This project utilizes Multiple Linear Regression (MLR) to predict house prices in King County, Washington, USA, using historical sales data. The dataset includes various features such as the number of bedrooms, square footage, views, and grades, with the goal of accurately predicting house prices.

roullette-simulations

Testing roulette simulations to find the most profitable strategy

stock-options

Analyzing, and developing trading strategies based on stock options data. It leverages powerful tools and libraries such as Jupyter Notebook, PostgreSQL, NumPy, Pandas, and Plotly to provide a robust platform for traders and analysts.