This is a Research Paper implementation of Levi-Hessaner Age-Gender Classification model which has re-implemented and trained on Indian faces.
Data structures & algorithms project for implementing the Hilbert R Tree data structure as present in the original research paper, focusing on the adding of elements and searching of elements along with a pre-order traversal of the tree.
QueensGambit is a Python-based chess engine using the Minimax algorithm with alpha-beta pruning to make optimal moves. It incorporates piece values inspired by AlphaZero and an entropy-based evaluation for dynamic gameplay. The engine supports both human-AI and AI-AI matches.
evoGrad is a lightweight automatic differentiation engine designed to help users understand autograd concepts and neural network operations. It offers a minimal framework for gradient computation and backpropagation, making it an ideal tool for beginners to explore deep learning fundamentals.
markoText is a Python-powered story generator using a Bag of Words Markov Chain model to craft narratives. By training on input text, it learns word transition probabilities to generate unique content mimicking the style and structure of the original.
noisOut is a DDPM-based implementation for generating high-quality images, inspired by Dhariwal & Nichol (2021) and Ho et al. (2020). Using a UNet architecture with Sinusoidal Position Embeddings, the model learns to reverse a diffusion process, progressively removing noise from images.
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chromaVive turns grayscale images into vibrant, colorized versions using advanced deep learning inspired by Richard Zhang's research at UC Berkeley. Powered by models from the ECCV16 and SIGGRAPH17 papers, chromaVive advances the art of image colorization.
echoGPT is a minimal GPT implementation for character-level language modeling with 25.4M parameters. Built with PyTorch, it includes multi-head self-attention, feed-forward layers, and position embeddings. Trained on text like tiny_shakespeare.txt to predict the next character.
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