Maschinelles Lernen · GitHub

Training and evaluating state-of-the-art deep learning CNN architectures for plant disease classification task.

Set up CUDA for machine learning (and gaming) on macOS using a NVIDIA eGPU

A tutorial on TensorFlow

MINE: Mutual Information Neural Estimation in pytorch (unofficial)

TensorFlow2.0 官方教程翻译，基本概念讲解、实战项目、TensorFlow2.0编程技巧。

This repository collates a number of MATLAB examples demonstrating Scientific Machine Learning (SciML) and Physics Informed Machine Learning.

Deep Learning Transformer models in MATLAB

Continual Hyperparameter Selection Framework. Compares 11 state-of-the-art Lifelong Learning methods and 4 baselines. Official Codebase of "A continual learning survey: Defying forgetting in classification tasks." in IEEE TPAMI.

pytorch implementation of the different DeepGaze models

This repository provides the code used to implement the framework to provide deep learning models with total uncertainty estimates as described in "A General Framework for Uncertainty Estimation in Deep Learning" (Loquercio, Segù, Scaramuzza. RA-L 2020).

Deep generative models of voxel grids for structure-based drug discovery

👨‍🔬 In Russian: Обновляемая структурированная подборка бесплатных ресурсов по тематикам Data Science: курсы, книги, открытые данные, блоги и готовые решения.

Official Code for Assem-VC @ICASSP2022

Official code for Cotatron @ INTERSPEECH 2020

Facial Expression or Facial Emotion Detector can be used to know whether a person is sad, happy, angry and so on only through his/her face. This Repository can be used to carry out such a task.

[W-NUT'20] Punctuation Restoration using Transformer Models for High-and Low-Resource Languages

A list of point cloud scene flow papers, codes and datasets.

OCR, Archive, Index and Search: Implementation agnostic OCR framework.

All lecture notes, slides and assignments from CS224n: Natural Language Processing with Deep Learning class by Stanford

Unofficial tensorflow implementation of real-time scene image segmentation model "BiSeNet V2: Bilateral Network with Guided Aggregation for Real-time Semantic Segmentation"

Flexible Feature visualization on PyTorch, for research and art :mag_right: :computer: :brain: :art:

Learning and Building Convolutional Neural Networks using PyTorch

A tool for efficient semi-supervised video object segmentation (great results with minimal manual labor) and a dataset for benchmarking