Project of Course SPH6004 Advanced Statistical Learning

Directory for the Tenserflow certification preparation. Tools: Google colab, Python, Scikit-learn

ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator

Fast and Accurate ML in 3 Lines of Code

Fit interpretable models. Explain blackbox machine learning.

A unified framework for machine learning with time series

This repository contains Dockerfiles, scripts, yaml files, Helm charts, etc. used to scale out AI containers with versions of TensorFlow and PyTorch that have been optimized for Intel platforms. Scaling is done with python, Docker, kubernetes, kubeflow, cnvrg.io, Helm, and other container orchestration frameworks for use in the cloud and on-premise

Flower: A Friendly Federated Learning Framework

Parallel computing with task scheduling

Machine Learning Containers for NVIDIA Jetson and JetPack-L4T

Intel(R) Extension for Scikit-learn is a seamless way to speed up your Scikit-learn application

FEDn: A production-grade, open federated learning framework. This repository contains the open source Python framework, CLI and API.

Open standard for machine learning interoperability

Machine Learning tasks involving the Titanic Dataset and Breast Cancer Wisconsin (Diagnostic) dataset

Time series forecasting with machine learning models

This repository contains all the machine learning and deep learning model I have implemented using various frameworks like keras, tensorflow, scikit-learn, pytorch, etc.

Data search & enrichment library for Machine Learning → Easily find and add relevant features to your ML & AI pipeline from hundreds of public and premium external data sources, including open & commercial LLMs

MLOps simplified. From ML Pipeline ⇨ Data Product without the hassle

An inference server for your machine learning models, including support for multiple frameworks, multi-model serving and more