Determined is an open-source machine learning platform that simplifies distributed training, hyperparameter tuning, experiment tracking, and resource management. Works with PyTorch and TensorFlow.

A simple, easy-to-understand library for diffusion models using Flax and Jax. Includes detailed notebooks on DDPM, DDIM, and EDM with simplified mathematical explanations. Made as part of my journey for learning and experimenting with state-of-the-art generative AI.

🔥 A tool for visualizing and tracking your machine learning experiments. This repo contains the CLI and Python API.

Modular Natural Language Processing workflows with Keras

To preform image classification on Rice Leaf Disease images using CNN via various methods.

An advanced platform for quantitative trading strategies, including AI-driven price prediction models and user management systems. Emulating institutional-grade practices like Citadel, it facilitates the development, training, and deployment of machine learning models for precise market forecasting.

Flatiron School Data Science Bootcamp Phase 4 Project

QKeras: a quantization deep learning library for Tensorflow Keras

EBOP Model Automatic input Value Estimation Neural network

Training Higgs Dataset with Keras

Open standard for machine learning interoperability

Libraries/ Tools/ Technologies/ Frameworks

Neural Networks, TensorFlow, Keras, Natural Language Processing

Visualizer for neural network, deep learning and machine learning models

Decadal prediction of climate data subject to different GHG emission scenarios using a variational autoencoder

Seasonal-level prediction of climate data with a variational autoencoder

These are examples of various types of data analysis. I hope my code will be helpful as it includes various processes from data preprocessing to results.

Implementations of ResNet-18, ResNet-34, ResNet-50, ResNet-101, and ResNet-152 in TensorFlow 2, based on the "Deep Residual Learning for Image Recognition" paper by Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun (2015)

Facial recognition in Python using Tensorflow

Build a robust image classifier using CNNs to efficiently classify different plant seedlings and weeds to improve crop yields and minimize human involvement