alexhock

alexhock's Stars

• Azure-Samples/azureai-samples

  Official community-driven Azure AI Examples

  Language:Jupyter Notebook198121

• microsoft/rag-experiment-accelerator

  The RAG Experiment Accelerator is a versatile tool designed to expedite and facilitate the process of conducting experiments and evaluations using Azure Cognitive Search and RAG pattern.

  Language:Python10535

• gaomingqi/Track-Anything

  Track-Anything is a flexible and interactive tool for video object tracking and segmentation, based on Segment Anything, XMem, and E2FGVI.

  Language:Python6.2k457

• microsoft/Data-Discovery-Toolkit

  A data discovery and manipulation toolset for unstructured data

  Language:Jupyter Notebook4811

• whitead/paper-qa

  LLM Chain for answering questions from documents with citations

  Language:Python3.7k352

• huangyueranbbc/RecommendByItemcf

  Hadoop mapreduce. 基于ItemCF的协同过滤 物品推荐系统 Collaborative filtering goods recommendation system based on ItemCF

  Language:Java2613

• alexhock/pixplotml

  A Visualization Tool for Image-based Machine Learning Projects - Great for object-detection and image classification projects

  Language:JavaScript212

• facebookresearch/ConvNeXt

  Code release for ConvNeXt model

  Language:Python5.6k677

• henrikbostrom/crepes

  Conformal classifiers, regressors and predictive systems

  Language:Python35828

• Chris-hughes10/Yolov7-training

  A clean, modular implementation of the Yolov7 model family, which uses the official pretrained weights, with utilities for training the model on custom (non-COCO) tasks.

  Language:Jupyter Notebook11335

• bepuca/azureml-scaffolding

  Language:Makefile286

• Chris-hughes10/pytorch-accelerated

  A lightweight library designed to accelerate the process of training PyTorch models by providing a minimal, but extensible training loop which is flexible enough to handle the majority of use cases, and capable of utilizing different hardware options with no code changes required. Docs: https://pytorch-accelerated.readthedocs.io/en/latest/

  Language:Python16121

• rmunro/pytorch_active_learning

  PyTorch Library for Active Learning to accompany Human-in-the-Loop Machine Learning book

  Language:Python908178

• modAL-python/modAL

  A modular active learning framework for Python

  Language:Python2.2k317

• huggingface/pytorch-image-models

  The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (ViT), MobileNetV4, MobileNet-V3 & V2, RegNet, DPN, CSPNet, Swin Transformer, MaxViT, CoAtNet, ConvNeXt, and more

  Language:Python30.3k4.6k

• microsoft/knowledge-extraction-recipes-forms

  Knowledge Extraction For Forms Accelerators & Examples

  Language:Jupyter Notebook21246

• facebookresearch/fairseq

  Facebook AI Research Sequence-to-Sequence Toolkit written in Python.

  Language:Python29.6k6.3k

• lucidrains/sinkhorn-transformer

  Sinkhorn Transformer - Practical implementation of Sparse Sinkhorn Attention

  Language:Python24821

• better/convoys

  Implementation of statistical models to analyze time lagged conversions

  Language:Python25541

• hfawaz/dl-4-tsc

  Deep Learning for Time Series Classification

  Language:Python1.5k542

• fastai/fastbook

  The fastai book, published as Jupyter Notebooks

  Language:Jupyter Notebook21k8.1k

• microsoft/RepPoints

  Represent Visual Objects by Point Sets

  Language:Python58374

• interpretml/interpret

  Fit interpretable models. Explain blackbox machine learning.

  Language:C++6.1k718

• TDAmeritrade/stumpy

  STUMPY is a powerful and scalable Python library for modern time series analysis

  Language:Python3.1k286

• ikivanc/Bot-Framework-and-OCR-Extract

  Bot Framework v4 and OCR Extract

  Language:C#113

• microsoft/AzureML-BERT

  End-to-End recipes for pre-training and fine-tuning BERT using Azure Machine Learning Service

  Language:Jupyter Notebook388126

• grobgl/rnnsm

  Language:Jupyter Notebook1817

• MLSurvival/MTLSA

  A Multi-Task Learning Formulation for Survival Analysis

  Language:Matlab1910

• PathologyDataScience/SurvivalNet

  Deep learning survival models

  Language:Python11345

• cwig/start_follow_read

  Language:Python7548