🎯Experienced Machine Learning/Data Scientist with a demonstrated history of working in the information technology and services industry.🫶 I love to solve complex data powered use cases by leveraging machine learning solutions and build software products that scale.Techstack: ✨Python (pandas, numpy, scikit-learn), SQL, PyTorch and Machine Learning - [Main] [6.5+ years]✨Microservices, Flask, Docker, Azure, AWS, CI/CD, GIT, Bash - [Proficient] [5.5+ years]✨Kubernetes, GCP, Big Data, Serverless Applications/Pipeline - [Learning] [4+ years]Fundamentals: DSA, System Design [6+ years]Please find below the niche of the projects I have done:❥ Recommender Systems: Knowledge based | Content based | Collaborative Filtering (user/item/hybrid)❥ Time Series Forecasting: Sales/Demand Forecasting for CPG/Pharma Fortune 100 companies, Anomaly Detection❥ Inventory Optimization/Prediction: Safety Stock Prediction/Lead Time Prediction❥ Financial Analytics/Customer Analytics❥ Detect Skin Cancer : Compared performance of CNN and VGG16 (Transfer Learning)❥ Face Generation using DCGAN ,Generate a Script using RNNs❥ Classical NLP: POS Tagging, Text Classification, Semantics & Sentiment Analysis, Topic Modeling etc. (Spacy | NLTK) ❥ Modern NLP: Embedding Look Up, (LLM) fine tuning of models employing Token Classification, Text Generation, Contrastive Learning etc. ❥ Built Containerized Microservice that fetches real time data from API, uses open source pre-trained sentiment DNN model and employs CI/CD.