6613 Open source projects that are alternatives of or similar to Interpret Text

Coding exercises for the Natural Language Processing concentration, part of Udacity's AIND program.

这是一款基于web的通用文本标注工具，支持大规模实体标注、关系标注、事件标注、文本分类、基于字典匹配和正则匹配的自动标注以及用于实现归一化的标准名标注，同时也支持文本的迭代标注和实体的嵌套标注。标注规范可自定义且同类型任务中可“一次创建多次复用”。通过分级实体集合扩大了实体类型的规模，并设计了全新高效的标注方式，提升了用户体验和标注效率。此外，本工具增加了审核环节，可对多人的标注结果进行一致性检验和调整，提高了标注语料的准确率和可靠性。

0xcert Framework - JavaScript framework for building decentralized applications - build something unique

Code accompanying the ECCV 2020 paper "Trajectron++: Dynamically-Feasible Trajectory Forecasting With Heterogeneous Data" by Tim Salzmann*, Boris Ivanovic*, Punarjay Chakravarty, and Marco Pavone (* denotes equal contribution).

Pytorch code for ECCV 2018 paper

An enhanced interactive Shell for Common Lisp (based on the Jupyter protocol)

Deep learning framework for wearable activity recognition based on convolutional and LSTM recurretn layers

Implementation of the Vanilla CNN described in the paper: Yue Wu and Tal Hassner, "Facial Landmark Detection with Tweaked Convolutional Neural Networks", arXiv preprint arXiv:1511.04031, 12 Nov. 2015. See project page for more information about this project. http://www.openu.ac.il/home/hassner/projects/tcnn_landmarks/ Written by Ishay Tubi : ishay2b [at] gmail [dot] com https://www.l

Code accompanying the blog post "Deep Reinforcement Learning with TensorFlow 2.1"

MAGIC (Markov Affinity-based Graph Imputation of Cells), is a method for imputing missing values restoring structure of large biological datasets.

Bonus materials, exercises, and example projects for our Python tutorials

TeachOpenCADD: a teaching platform for computer-aided drug design (CADD) using open source packages and data

Real Time Big Data / IoT Machine Learning (Model Training and Inference) with HiveMQ (MQTT), TensorFlow IO and Apache Kafka - no additional data store like S3, HDFS or Spark required

统计学习方法训练营课程作业及答案，视频笔记在线阅读地址：https://relph1119.github.io/statistical-learning-method-camp

Machine Learning and Deep Learning Resources

My personal notes, presentations, and notebooks on everything Deep Learning.

Dense Depth for Autonomous Driving (DDAD) dataset.

Convolutional Neural Network for Multi-label Multi-instance Relation Extraction in Tensorflow

Machine Learning Ops Workshop with SageMaker: lab guides and materials.

Machine Learning Model for Sport Predictions (Football, Basketball, Baseball, Hockey, Soccer & Tennis)

These are my learning exercices from Coursera

Deep learning for MIR

Exploration of methods for coloring t-SNE.

Fast and memory-efficient clustering

Think DSP: Digital Signal Processing in Python, by Allen B. Downey.

Lightweight and Lightning-Fast ⚡️ Pinyin Library for JavaScript

An MLOps framework to package, deploy, monitor and manage thousands of production machine learning models

A python tutorial on bayesian modeling techniques (PyMC3)

Deep Learning with TensorFlow 2 and Keras, published by Packt

SuperComputing 2017 Deep Learning Tutorial

Create interactive webpages from Jupyter Notebooks

Respository for Open-Science modular microscope system.

Data from the largest and longest measurement of online tracking.

AI-related tutorials. Access any of them for free → https://towardsai.net/editorial

(Tout langage) API compatible Pronote 2020/2021

Train and Deploy Simple Machine Learning Model With Web Interface - Docker, PyTorch & Flask

Tensorflow 2.0 Notes 提供了TF2.0案例实战以及TF2.0基础实战，目标是帮助那些希望和使用Tensorflow 2.0进行深度学习开发和研究的朋友快速入门，其中包含的Tensorflow 2.0教程基本通过测试保证可以成功运行(有问题的可以提issue，笔记网站正在建设中)。

Jupyter notebooks associated with the Algorithms for Optimization textbook

An interactive heatmap visualization built using D3.js

All course materials for the Zero to Mastery Deep Learning with TensorFlow course.

Visualisation tool for CNNs in pytorch

Data Engineering on Google Cloud Platform

Implementation of Deep Deterministic Policy Gradients using TensorFlow and OpenAI Gym

Jupyter Notebooks with Deep Learning Tutorials

Devenez Data-Scientist sur Le Wagon On Demand

Bu çalışma araştırmalar yaparken benzerlerine rastlayıp iyileştirerek derlemeye çalıştığım ve derin öğrenme (deep learning) konusunda kısa bir özet ve bolca kaynak yönlendirmesi olan (hatta sonunda koca bir liste var) hızlıca konuya giriş yapılabilinmesi için gereklilikleri özetlemektedir. Lütfen katkı vermekten çekinmeyin 👽

Ray tutorials from Anyscale

The Los Angeles Times' independent tally of coronavirus cases in California.

Find lane lines on the road using Python and OpenCV, applying Canny edge detectors and Hough line transforms

A delightful and complete interface to GitHub's amazing API

BAND：BERT Application aNd Deployment，Simple and efficient BERT model training and deployment, 简单高效的 BERT 模型训练和部署

A TensorFlow implementation of Multi-digit Number Recognition from Street View Imagery using Deep Convolutional Neural Networks (http://arxiv.org/pdf/1312.6082.pdf)

💎 数学公式识别

This is the code for "Bitcoin Prediction" by Siraj Raval on Youtube

An automatic beatmap generator using Tensorflow / Deep Learning.

Repository for coursera specialization Applied Data Science with Python by University of Michigan

Code for the paper "PortraitNet: Real-time portrait segmentation network for mobile device" @ CAD&Graphics2019

A tutorial for MNIST handwritten digit classification using sklearn, PyTorch and Keras.