Project Showroom is a curated collection of diverse machine learning, data science, and software development projects, showcasing advanced techniques, reusable templates, and real-world applications. This repository serves as both a professional portfolio and a reference for coding best practices, designed for me as a developer to streamline project development and implementation.
- Machine Learning Pipelines: End-to-end workflows for tasks like rental price prediction, customer churn analysis, and multilingual sentiment analysis.
- Deep Learning Applications: Projects on image classification, sentiment analysis, neural machine translation, and more, leveraging frameworks like TensorFlow and PyTorch.
- NLP and Text Processing: Sentiment analysis, translation pipelines, and part-of-speech tagging using state-of-the-art transformer models.
- MLOps Demonstrations: Integration of tools like MLflow, Weights & Biases, and FastAPI for scalable, production-ready solutions.
- Recommendation System: How to develop a recommendation system from the ground up (starting with a simple approach to more complex models)
- Code Templates: Reusable components for data cleaning, preprocessing, model evaluation, and API deployment.
This repository is a professional showcase for potential clients, providing:
- Ready-to-use templates and code snippets.
- Examples of well-documented and structured solutions.
- Insights into my approach to solving real-world problems with modern tools and techniques.
Explore the projects to see how cutting-edge technology meets practical implementation. Whether you're interested in data science, machine learning, or software engineering, this repository demonstrates the depth and versatility of my work.