My Personal Projects
Overview
This document provides an overview of key projects I have undertaken, showcasing my skills and expertise in various domains.
Project 1: minimalai - A Flexible Deep Learning Framework
Overview
Building a custom Deep Learning framework, ‘MinimalAI’, entirely from scratch using Python. The goal of this project is to develop a flexible deep learning framework that can be easily adapted for different use cases. This showcases progression from foundational concepts to achieving stable diffusion in deep learning.
Key Technologies
- Python
- PyTorch
- Diffusers
- einops
- timm
- datasets
- fastcore
- matplotlib
Project Highlights
Building a flexible Deep Learning framework from scratch. From Deep Learning foundations to building Stable Diffusion. This includes, - Creating Dataloaders and Datasets - Using Callbacks - Convolutions - Flexible Learner - Initialization methods - Activations - Optimizers - Augmentations - Attention based Stable Diffusion(DDPM, DDIM, VAE, Latents)
Outcome
This framework can be customized and used anywhere to build, train, evaluate Deep Learning models.
Project 2: Oracle Cloud - RAG Application based on LLAMA 2
Overview
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Key Technologies
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Project Highlights
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Outcome
Discuss the overall outcome and impact of the project, including any measurable results or achievements.
Project 3: Title of Project 3
Overview
Provide a brief overview of the project, including its purpose, goals, and context.
Key Technologies
List the key technologies, tools, and programming languages used in the project.
Project Highlights
Highlight notable aspects of the project, such as challenges faced, innovative solutions implemented, or unique features developed.
Outcome
Discuss the overall outcome and impact of the project, including any measurable results or achievements.