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younis-ali/README.md

Hi there, I'm Younis Ali 👋

Welcome to my GitHub profile! I'm a highly motivated and experienced Data Scientist and lifelong learner with a strong background in statistical analysis, machine learning, and data visualization. With 4 years of experience in the Data Science domain, I focus on Machine Learning model deployments, research, and LLM. I have a proven ability to turn large and complex data sets into actionable insights and solutions for businesses and organizations.

About Me

I thrive on solving complex problems and continuously expanding my knowledge in the ever-evolving fields of data science and artificial intelligence. With a focus on practical applications and research, I aim to leverage technology to drive innovation and create impactful solutions.

Expertise

  • Machine Learning (ML): Developing and deploying ML models for various applications.
  • Deep Learning: Designing and implementing neural networks for complex tasks.
  • Research: Conducting extensive research in advanced ML techniques, including GANs and adversarial training.
  • MLOps: Streamlining ML workflows and deploying scalable solutions.
  • Frappe Framework: Developing applications and tools using the Frappe framework.
  • ERPNext: Implementing ERP solutions and customizing modules to meet business needs.
  • Generative AI: Creating generative models and leveraging them for innovative solutions.
  • Prompt Engineering: Crafting effective prompts for language models.
  • Python: Proficient in Python for data analysis, machine learning, and web development.
  • JavaScript (JS): Experienced in front-end and back-end development using JavaScript.

Languages and Tools

Python JavaScript Frappe ERPNext AWS FastAPI OpenAI LangChain GCP PyTorch pandas numpy scikit-learn SQL Docker Airflow Git PostgreSQL Google Dialogflow Sagemaker HuggingFace Keras AutoGluon

Projects

1. Sales and Inventory Forecasting Data Engine Tool

Technologies: AWS Sagemaker, FastAPI, Frappe, ERPNext, Python, numpy, pandas, AutoGluonTS
Description: Led a team in designing and developing a tool for forecasting sales and inventory. Developed machine learning models for the given data and deployed them in FastAPI. Utilized AWS Sagemaker for machine learning, FastAPI for the backend, and Frappe and ERPNext for the frontend.

2. Conversational AI for Data Analytics and Business Intelligence

Technologies: LangChain, OpenAI, FastAPI, SQLite, Python, LLM
Description: Developed a Conversational AI system for data analytics and business intelligence using LangChain and leveraging OpenAI for natural language processing.

3. Time Series Forecasting Research

Technologies: Advanced deep learning techniques, Generative AI, Google Colab
Description: Conducted research on time series forecasting, exploring advanced deep learning techniques and Generative AI. Presented and published findings in an IEEE international conference.

4. Google Chat Summarization and Data Analyzer Tool

Technologies: FastAPI, Frappe, OpenAI, HuggingFace LLM
Description: Developed a tool for summarizing Google chat conversations and analyzing data. Used FastAPI and Frappe for development, and integrated OpenAI and HuggingFace LLM for natural language processing and analysis.

5. Online Classroom Analytics Services

Technologies: FastAPI, Visual analytics using Deep Learning, data representation
Description: Made substantial contributions to visual analytics services for online classroom software, enhancing data representation and insights for users.

6. Chatbot Development for User Interaction and Student Career Recommendations

Technologies: Google Dialogflow CX, FastAPI, PostgreSQL
Description: Utilized Google Dialogflow CX to craft chatbots for enhancing user interaction and providing student career recommendations. Developed FastAPI to drive chatbot functionality, with PostgreSQL used for the database.

7. Question Answering System in FastAPI

Technologies: FastAPI, HuggingFace LLM models
Description: Implemented a Question Answering system in FastAPI, leveraging HuggingFace LLM models for accurate responses.

8. ML Development of GANs and Variational Autoencoders

Technologies: GANs, Variational Autoencoders, Keras, PyTorch, Google Colab
Description: Conducted research and developed machine learning models, focusing on GANs, adversarial training, and adversarial attacks. Identified problems and surveyed the literature to understand existing approaches. Developed state-of-the-art models to solve identified problems in training GANs and improving robustness against adversarial attacks.

Education

  • Masters in Computer Science - University Of Kashmir, Srinagar

Get in Touch

Feel free to reach out if you have any questions, ideas, or collaboration opportunities. I'm always open to discussing new projects and exploring innovative solutions.

GitHub Stats

Your GitHub Stats

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  1. rag-pipeline-app rag-pipeline-app Public

    Implement RAG using LangChain and HuggingFace embedding models

    Jupyter Notebook 1

  2. lupus-patients-data-pipeline lupus-patients-data-pipeline Public

    EDA, pipelining and Analysis on a sample health data

    Jupyter Notebook 2

  3. ai-code-tester ai-code-tester Public

    This project provides an AI-driven test case generator using FastAPI. The application accepts a GitHub repository name and generates test cases for the repository using openAI LLM.

    Python 7

  4. airport-automation airport-automation Public

    The Airplane Mode app is a Frappe-based custom application designed to manage flight ticket systems. The app includes functionalities for managing airlines, airplanes, airports, flights, and passen…

    Python 1 1

  5. prompt-engineering-basics prompt-engineering-basics Public

    This repository covers the basis of prompt engineering using LangChain and OpenAI.

    Jupyter Notebook 1 1

  6. market-research-agent market-research-agent Public

    Market Research Agent app, with a focus on opposition research (competitor analysis).

    Python 4