Welcome to my GitHub profile! I'm a passionate Data Scientist with expertise in Python, Machine Learning, Deep Learning, Computer Vision, Big Data, Power BI, Statistics, and Web Development. I love solving complex problems and building intelligent systems using data-driven approaches. Here's a glimpse of what I do:

• 🔭 I’m currently working on AI and ML projects in healthcare, finance, and e-commerce sectors.
• 🌱 I’m continuously learning advanced techniques in Deep Learning, Big Data, and Web Development.
• 💬 Ask me about anything related to data science, Python, machine learning, and AI.
• 💡 I’m interested in applying AI for social good, including healthcare and sustainability projects.
• 📫 Reach me at: vikalp026varshney@gmail.com or connect with me on LinkedIn

• Python: My primary language for data analysis, machine learning, deep learning, and web development.
• SQL: Querying databases and handling large datasets.
• JavaScript/HTML/CSS: For building interactive web applications.

• Scikit-learn: Feature engineering, model training, and evaluation.
• TensorFlow & Keras: Building and deploying deep learning models.
• XGBoost & CatBoost: Gradient boosting models for classification and regression.
• NLP: Text analysis and natural language understanding.
• RAG (Retrieval-Augmented Generation): Using transformer models to augment responses.

• Convolutional Neural Networks (CNNs): For image classification, object detection, and segmentation tasks.
• OpenCV: Image processing and computer vision tasks.
• YOLO: Real-time object detection.

• Hadoop & Spark: Processing and analyzing large datasets efficiently.
• Power BI & Tableau: Data visualization and business intelligence tools.
• SQL & NoSQL Databases: MongoDB, MySQL, PostgreSQL for storing and querying data.

• Flask: Building web applications for data science projects.
• HTML/CSS/JavaScript: Front-end development for data visualization and interaction.
• Docker: Containerizing and deploying machine learning models and applications.

• Descriptive & Inferential Statistics: Hypothesis testing, correlation analysis, regression models.
• Pandas & NumPy: For data manipulation and numerical computation.
• Matplotlib & Seaborn: For visualizing insights from data.

Here are some projects that showcase my skills:

• Web Scraping — Technologies: Python, Flask, AWS, Git

  • Utilized Python as the primary programming language, leveraging libraries such as BeautifulSoup and Selenium to automate the data extraction process.
  • Developed efficient scraping scripts that navigated website structures, interacted with elements, and collected structured data from Flipkart with precision.

• Diamond Price Prediction — Technologies: Python, Machine Learning, Flask, Docker, AWS, DVC, Git, MLflow, Airflow

  • Achieved an accuracy of 97% using ML algorithms such as XGBoost, Lasso, and AdaBoost.
  • Developed a web application using Flask and Docker.

• Development Of An AI Powered Chatbot For Automated Code Generation — Technologies: Transformer, FAISS, LLM

  • Developed an AI-powered system for automated code generation using the Retrieval-Augmented Generation (RAG) technique, integrating a transformer model for information retrieval and the GEMMA LLM for code generation.
  • Trained the transformer model on the English-Python dataset and fine-tuned the GEMMA LLM using the FlyTech-25 dataset, utilizing FAISS as a vector database for efficient retrieval.
  • Created an end-to-end web application featuring a user-friendly interface and robust backend services, supporting functionalities such as user authentication, data management, and interactive elements to enhance user experience.

• Telegram Question Answering Chatbot — Technologies: Aiogram, BotFather, SerpAPI, GPT API, Langchain

  • Developed a Telegram chatbot using Aiogram and BotFather, integrating GPT API for natural language processing and SerpAPI for web search capabilities.
  • Created an end-to-end application that allows users to ask questions and receive instant answers, leveraging Langchain for enhanced dialogue management and context handling.

• Text Summarization Using LLM — Technologies: NLP, Hugging Face Hub, Flask, Docker, Git, AWS

  • Implemented a text summarization solution using the Google Pegasus model from Hugging Face, trained on the Samsum dataset for effective summarization of dialogue-based content.
  • Deployed the application on AWS for reliable hosting, enabling users to access the service from anywhere. Check out my repositories to explore more of my work! 🚀

• LinkedIn: Vikalp Varshney
• Email: vikalp026varshney@gmail.com