Puranjan Bandyopadhyaya-Internship - Generative AI
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Experience
Internship - Generative AI
Continental
- Gathered tire images and their feature descriptions.
- Cleaned dataset of image metadata using pandas.
- Stored image feature embeddings in Chroma vector db.
- Used image augmentations to increase dataset size.
- Used sklearn to create shuffled datasets and imbalanced-learn to balance class sizes in dataset.
- Used PyTorch to train and test different neural networks.
- Validated model using custom accuracy metric based on similarity search in ChromaDB.
- Visualized accuracy predictions using matplotlib.
- Plugged trained model into DreamBooth to train stable diffusion model and generate new images of tires.
- Created custom Docker image in Amazon Elastic Container Registry for machine learning script.
Master of Science in Artificial Intelligence
Friedrich-Alexander-Universität Erlangen-Nürnberg
Data Scientist Foundations Nanodegree
Udacity
- Analyzed data related to bike share systems in Chicago, New York City and Washington using Python scripts to compute statistics such as most popular times of travel, stations and trips, average and total trip durations, and counts of user types.
- Gathered, analyzed and cleaned a Twitter archive of WeRateDogs using pandas, NumPy, requests, tweepy and json; used a neural network to predict breed from live Twitter data.
- Trained, tested and evaluated machine learning models using sklearn in Python and Jupyter Notebook to determine house prices based on features like transport facility and crime rates.
- Performed principal component analysis to identify customer segments; applied transformations and implemented clustering algorithms to segment and label data.
- Utilized Python libraries NumPy, pandas, scikit-learn and matplotlib.
Application Development Associate
Accenture Solutions Private Limited
- Completed several projects independently, collaborating with cross functional international client teams at DOW Chemicals.
- Implemented end-to-end SAP PO integrations supporting chemical plant order processing and associated financial transactions with banking systems.
Bachelor of Technology in Computer Science & Engineering
KIIT University
Industry Experience
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Experienced in Education, Chemical, Information Technology, Automotive, and Manufacturing.
Business Area Experience
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Experienced in Information Technology, Research and Development, Finance, Operations, Product Development, and Business Intelligence.
Summary
- MSc student in Artificial Intelligence at Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU).
- Proficient in Python, with experience in data analytics and deep learning using PyTorch.
- Strong foundation in machine learning and deep learning, including advanced topics such as transformers, diffusion models, and their application in large language models (LLMs). Relevant coursework: Advanced Deep Learning, Explainable Machine Learning.
- Hands-on experience in Generative AI through a 6-month internship at Continental.
- Applied Generative AI in a project to build an AI coding assistant using LLaMA-based LLMs with Retrieval-Augmented Generation (RAG), leveraging LlamaIndex, LlamaParse, and Ollama.
Skills
- Pytorch
- Python Dsci/ml Libraries (Numpy, Pandas, Sklearn, Scipy)
- Deep Learning
- Machine Learning
- Llm
- Git
Languages
Education
Friedrich-Alexander-Universität Erlangen-Nürnberg
Master of Science in Artificial Intelligence · Artificial Intelligence · Erlangen, Germany
KIIT University
Bachelor of Technology in Computer Science & Engineering · Computer Science & Engineering · Bhubaneswar, India
Certifications & licenses
Data Scientist Foundations Nanodegree
Udacity
Statistics
Experience
Global Experience
Expertise
Qualifications
Profile
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