A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.
Обновлено 2024-11-17 23:49:19 +03:00
An example of using OpenCV dnn module with YOLOv5. (ObjectDetection, Segmentation, Classification)
Обновлено 2024-11-11 20:00:01 +03:00
The 'Unified Labeling Support Tool' provides the functionality to reset all corresponding client services (UL, AIP, MIP, etc.). Its main purpose is to delete the currently downloaded sensitivity label policies and thus reset all settings, and it can also be used to collect data for failure analysis and problem solving.
Обновлено 2024-11-04 11:03:45 +03:00
The ORBIT dataset is a collection of videos of objects in clean and cluttered scenes recorded by people who are blind/low-vision on a mobile phone. The dataset is presented with a teachable object recognition benchmark task which aims to drive few-shot learning on challenging real-world data.
Обновлено 2024-08-13 03:27:45 +03:00
This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows".
Обновлено 2024-07-15 18:00:32 +03:00
Experience, Learn and Code the latest breakthrough innovations with Microsoft AI
Обновлено 2024-06-26 22:42:37 +03:00
Multi-species bioacoustic classification using deep learning algorithms
Обновлено 2024-06-18 01:58:08 +03:00
Workshop for student hackathons focused on Lobe.ai
Обновлено 2024-01-09 08:40:23 +03:00
A web app to create and browse text visualizations for automated customer listening.
Обновлено 2023-10-27 06:29:49 +03:00
With AutoBrewML Framework the time it takes to get production-ready ML models with great ease and efficiency highly accelerates.
Обновлено 2023-08-03 09:43:02 +03:00
Inverted file indexing and retrieval optimized for short texts. Supports auto-suggest and query segment classification.
Обновлено 2023-06-12 23:26:47 +03:00
Text classification solution with Microsoft Machine Learning Server
Обновлено 2023-06-12 22:32:06 +03:00
Code for the neural architecture search methods contained in the paper Efficient Forward Neural Architecture Search
Обновлено 2023-06-12 21:22:32 +03:00
Documentation and example code for DCASE 2019 task 5 sound classification challenge
Обновлено 2023-06-12 21:21:43 +03:00
Deep Metric Transfer for Label Propagation with Limited Annotated Data
Обновлено 2023-06-03 07:09:23 +03:00
Intelligent APIs aim to make machine learning (ML) tasks easier for UWP developers to leverage in their applications without needing ML expertise or creating a new model.
Обновлено 2023-02-10 22:43:48 +03:00
This is an official implementation for "SimMIM: A Simple Framework for Masked Image Modeling".
Обновлено 2022-09-29 18:17:40 +03:00
This is an official implementation of CvT: Introducing Convolutions to Vision Transformers.
Обновлено 2022-06-22 07:21:09 +03:00
Обновлено 2022-01-12 03:35:14 +03:00
Ramp up your custom natural language processing (NLP) task, allowing you to bring your own data, use your preferred frameworks and bring models into production.
Обновлено 2022-01-10 02:07:54 +03:00
This is a classification solution accelerator to help you build and deploy a binary classification project.
Обновлено 2021-10-01 18:41:37 +03:00
Classification Mapping
Обновлено 2021-05-13 14:53:42 +03:00
Quantum Classification tutorial using Microsoft Quantum Development Kit
Обновлено 2020-12-03 10:04:00 +03:00
Tutorial demonstrating how to create a semantic segmentation (pixel-level classification) model to predict land cover from aerial imagery. This model can be used to identify newly developed or flooded land. Uses ground-truth labels and processed NAIP imagery provided by the Chesapeake Conservancy.
Обновлено 2019-07-25 06:53:28 +03:00