Python-based research interface for blackbox and hyperparameter optimization, based on the internal Google Vizier Service.

SkyPilot: Run LLMs, AI, and Batch jobs on any cloud. Get maximum savings, highest GPU availability, and managed execution—all with a simple interface.

Propulate is an asynchronous evolutionary optimization algorithm and software package for global optimization and hyperparameter search on high-performance computers.

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

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

Predicting employee salaries based on job type, degree, major, industry, years of experience, and distance from a metropolis using machine learning techniques.

Bayesian optimization using Gaussian Process regression (Python)

A summative coursework for CSC8635 Machine Learning with Project

Streamlining reinforcement learning with RLOps. State-of-the-art RL algorithms and tools.

Automated Machine Learning on Kubernetes

EvalML is an AutoML library written in python.

A training framework for Stable Baselines3 reinforcement learning agents, with hyperparameter optimization and pre-trained agents included.

ML project focused on predicting Titanic passenger survival using various algorithms and extensive data analysis techniques. This project includes detailed data visualization and interpretation to uncover key factors affecting survival. By leveraging various ML models the analysis aims to achieve high predictive accuracy.

The project discusses using machine learning to predict doctoral program admissions and compares the performance of Logistic Regression and KNN models, finding that KNN outperforms Logistic Regression.

Sequential model-based optimization with a `scipy.optimize` interface

Additional stoppers for ray tune

A convenient way to trigger synchronizations to wandb / Weights & Biases if your compute nodes don't have internet!

Testing ray tune with slurm batch submission and optuna and wandb

🔍✨ A machine learning project that predicts income based on various demographic factors using Random Forest and Gradient Boosting algorithms. Includes data preprocessing, hyperparameter tuning, and model evaluation with detailed performance metrics. 📊🤖

Data Science Project - Full Depth analysis AND Prediction Using Decision Tree and Random Forest