Popular GitHub Repositories for Kernel Pca

AiLearning：数据分析+机器学习实战+线性代数+PyTorch+NLTK+TF2

10 Lessons to Get Started Building AI Agents

H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.

A collection of important graph embedding, classification and representation learning papers with implementations.

Book_5_《统计至简》 | 鸢尾花书：从加减乘除到机器学习；上架！

FlashInfer: Kernel Library for LLM Serving

A C#/.NET library to run LLM (?LLaMA/LLaVA) on your local device efficiently.

It is open source ebook about TensorFlow kernel and implementation mechanism.

Fast and Easy Infinite Neural Networks in Python

Kernl lets you run PyTorch transformer models several times faster on GPU with a single line of code, and is designed to be easily hackable.

Five lessons, learn how to really apply AI to your .NET Applications

High-fidelity performance metrics for generative models in PyTorch

[CVPR'24] UniRepLKNet: A Universal Perception Large-Kernel ConvNet for Audio, Video, Point Cloud, Time-Series and Image Recognition

:metal: TT-NN operator library, and TT-Metalium low level kernel programming model.

A parallel implementation of "graph2vec: Learning Distributed Representations of Graphs" (MLGWorkshop 2017).

FP16xINT4 LLM inference kernel that can achieve near-ideal ~4x speedups up to medium batchsizes of 16-32 tokens.

[CVPR 2023 Highlight] Neural Kernel Surface Reconstruction

Sample to envision intelligent apps with Microsoft's Copilot stack for AI-infused product experiences.

Code for our CVPR 2019 paper: Selective Kernel Networks; See zhihu：https://zhuanlan.zhihu.com/p/59690223

AI-in-a-Box leverages the expertise of Microsoft across the globe to develop and provide AI and ML solutions to the technical community. Our intent is to present a curated collection of solution accelerators that can help engineers establish their AI/ML environments and solutions rapidly and with minimal friction.