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Hi there 👋, I am Chitral Patil ! 😁

I am an Entrepreneurial AI/ML Software Engineer with a foundation in computer engineering, currently pursuing master's in Data Science at SUNY Buffalo. Co-founder of Propael, a game-changing job application tool, with a rich background in Silicon Valley startups and large-scale data pipeline architecture.

In the heart of Silicon Valley's dynamic startup ecosystem, I've carved a niche for myself as a forward-thinking Data Scientist and Entrepreneur. My journey began during my undergraduate studies in computer engineering, where I picked elective subjects that revolved around data science like Machine Learning, NLP, Artificial Intelligence & Soft Computing, Big Data & Analytics, and Data Warehousing & Mining. Motivated by these experiences, I am now pursuing a master's degree in data science from the University at Buffalo.

My journey is a blend of deep technical expertise and sharp business acumen, making me adept at both coding and understanding the nuances of the market. At CYQIQ, an early-stage startup, I wore multiple hats - from an AI/ML Software Engineer to diving deep into entrepreneurial realms. I honed skills beyond coding, delving into customer discovery, market sizing, and direct interactions with clients. This holistic experience has been instrumental in shaping my vision and approach.

My passion project, Propael, stands as a testament to my commitment to innovation. As a Chrome extension, Propael is revolutionizing job applications by offering one-click automation for ATS-friendly cover letters, providing exclusive insights like pinpointing the exact years of experience required for a job, and delivering tailored content through our unique RAG Architecture. We're not just another tool; we're a game-changer, recognized with the blue tick on the Google Chrome Webstore and proudly holding the Established Publisher Badge. With over 100 daily active users, we're making a tangible difference in the job application process.

Parallelly, as a Graduate Research Assistant, I've been instrumental in architecting data pipelines for a staggering 2.5 TB of data. My focus on fraud detection isn't just about data crunching; it's about optimizing storage and ensuring the integrity of the information we handle.

In essence, I'm not just a technologist; I'm a problem solver, an innovator, and a visionary entrepreneur. Always eager to connect with fellow trailblazers and disruptors. Let's shape the future together!

Languages and Tools:

React   FastAPI   MongoDB   JavaScript   Python   C   Pandas   Numpy   Scikitlearn   Tensorflow   HTML5   CSS3   jQuery   Bootstrap   MySQL   Git   GitHub   LATEX  

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Chitral Patil's Projects

accounting-and-auditing-enforcement-releases-web-scraper icon accounting-and-auditing-enforcement-releases-web-scraper

Unlock valuable insights from accounting and auditing enforcement releases effortlessly with my web scraper. Gain access to critical data, track regulatory actions, and stay informed. Simplify your research process and make data-driven decisions with my code.

etl-edgar-10-k-filings-archive icon etl-edgar-10-k-filings-archive

This repository features a powerful cloud-based crawler capable of meticulously compiling paths to HTML files and organizing them in a dictionary, efficiently categorized by tickers. This ready-to-use dictionary facilitates seamless extraction, transformation, and loading (ETL) processes, streamlining further data analysis workflows.

etl-sec-edgar-10-k-filings icon etl-sec-edgar-10-k-filings

ETL-10-K-Filings is a Python-based open-source project designed for ETL of financial data from SEC Edgar filings. Focusing on the MDA Section, the project adeptly processes data for over 10,000 publicly traded companies, leveraging advanced parsing techniques and multi-threading for optimal performance.

guestbook icon guestbook

The place where future contributors are born

house-price-prediction-cicd-deployment icon house-price-prediction-cicd-deployment

Built with Dockerfile for containerization and a Procfile for deployment on Heroku, this app uses a linear regression model and pickled files for optimal performance. Featuring CI/CD for reliable results, my app is built in flask where trained model and feature scaling information comes from the pickled files.

movie-recommender-system-fastapi-react.js icon movie-recommender-system-fastapi-react.js

I have built a powerful movie recommender system that uses content-based filtering. It's built with Python, FastAPI, and React.js, and has a clean and organized folder structure for easy contribution. The backend uses Pandas, NumPy, and scikit-learn, while the frontend uses React.js and axios.

reinforcement-learning-web-app icon reinforcement-learning-web-app

A thrilling treasure hunt awaits in this project! Explore the Treasure Hunt Environment, challenge the Random Agent, and witness the intelligence of SARSA and Q-Learning agents as they navigate the grid-world.

sec-edgar-scraper icon sec-edgar-scraper

This repository contains Python scripts for scraping financial data from the SEC website. The scripts use requests and pandas modules to download and parse financial data from filings submitted to the SEC by publicly traded companies. The script downloads and formats company metadata company facts data, and company concept data.

sms-spam-classifier icon sms-spam-classifier

Deployed on Heroku, this repository contains a machine learning model and web app for classifying text messages as "spam" or "ham". With clear instructions and all necessary files included, deploying the app locally or on Heroku is straightforward. An ideal repository for recruiters seeking a skilled developer in machine learning & web development.

textextend-ai icon textextend-ai

This repository contains a Python script that transforms a PDF document into an elegant Word document using OpenAI's GPT-3 language model. The script provides a user-friendly interface for uploading PDF files, entering system names, and composing prompts. The resulting Word document can be freely edited and customized by the user.

university-at-buffalo-faculty-web-scraper icon university-at-buffalo-faculty-web-scraper

A Python web scraping tool to extract data from a faculty directory website. It retrieves faculty information like names, colleges, email addresses, subjects taught, and research topics. Data can be exported to CSV for further analysis.

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