samiNCL's starred repositories

electron

:electron: Build cross-platform desktop apps with JavaScript, HTML, and CSS

peerjs

Simple peer-to-peer with WebRTC.

Language:TypeScriptLicense:MITStargazers:12173Issues:246Issues:903

bertviz

BertViz: Visualize Attention in NLP Models (BERT, GPT2, BART, etc.)

Language:PythonLicense:Apache-2.0Stargazers:6608Issues:71Issues:123

blazer

Business intelligence made simple

Language:RubyLicense:MITStargazers:4438Issues:73Issues:289

digital-gardeners

Resources, links, projects, and ideas for gardeners tending their digital notes on the public interwebs

Language:JavaScriptLicense:MITStargazers:3886Issues:94Issues:12

annotator

Annotation tools for the web. Select text, images, or (nearly) anything else, and add your notes.

Language:JavaScriptLicense:NOASSERTIONStargazers:2672Issues:150Issues:552

dotfiles

config files for zsh, bash, completions, gem, git, irb, rails

Language:ShellLicense:MITStargazers:2310Issues:40Issues:12

machine-learning-yearning

Machine Learning Yearning book by 🅰️𝓷𝓭𝓻𝓮𝔀 🆖

anystyle

Fast citation reference parsing

Language:RubyLicense:NOASSERTIONStargazers:997Issues:33Issues:202

xAPI-Spec

The xAPI Specification describes communication about learner activity and experiences between technologies.

keras-nlp

Modular Natural Language Processing workflows with Keras

Language:PythonLicense:Apache-2.0Stargazers:738Issues:29Issues:607

telegraph

Telegraph is a Laravel package for fluently interacting with Telegram Bots

Language:PHPLicense:MITStargazers:649Issues:10Issues:229

chat-miner

Parsers and visualizations for chats

Language:PythonLicense:MITStargazers:565Issues:10Issues:50

explorableexplanations.github.io

The Explorable Explanations Website

Language:JavaScriptLicense:CC0-1.0Stargazers:460Issues:30Issues:15
Language:TypeScriptLicense:NOASSERTIONStargazers:256Issues:5Issues:2

Speech2Face

Implementation of the CVPR 2019 Paper - Speech2Face: Learning the Face Behind a Voice by MIT CSAIL

Language:PythonLicense:MITStargazers:163Issues:12Issues:5

trunklucator

Python module for data scientists for quick creating annotation projects.

Language:PythonLicense:Apache-2.0Stargazers:82Issues:5Issues:1

coscripter-extension

CoScripter Firefox browser extension

Language:JavaScriptLicense:NOASSERTIONStargazers:19Issues:7Issues:1

emotion-detection-from-text-python

Emotion Detection from Text

Language:Jupyter NotebookLicense:MITStargazers:12Issues:2Issues:0

Self-driving-car-Nanodegree

Learning to build the future, today! Self-driving cars represent one of the most significant advances in modern history. Their impact will go beyond technology, beyond transportation, beyond urban planning to change our daily lives in ways we have yet to imagine. Here are some considerations: self-driving vehicles will save a lot of lives they will make our lives also more comfortable (e.g. mobility for seniors) transport will be delivered as a service from companies who own fleets of self-driving vehicles transportation will become more tightly integrated and packaged into many services premium vehicle services will be available being able to avoid crashes will change the vehicle body construction radically interior equipment will focus even more on comfort emotion (max. speed, acceleration, handling, exterior design ..) might almost entirely leave transportation are parking lots or parking spaces in town centers necessary anymore? traffic flow will be better regulated infrastructure utilization will be optimized a hugh amount of data will be collected and used hacking of vehicles will be a serious issue ... In this program you could learn the skills and techniques used by self-driving car teams at the most innovative companies in the world like NVIDIA, Mercedes-Benz, Uber ATG, Elektrobit. This amazing technology is practiced through interactive projects in computer vision, robotic controls, localization, path planning, machine learning and more.

Language:Jupyter NotebookStargazers:6Issues:2Issues:0

distance_learning

Sentiment analysis on the tweets about distance learning with TextBlob

Language:Jupyter NotebookStargazers:5Issues:1Issues:1

SRL

DAACS Self-Regulated Learning Lab

Language:ShellStargazers:2Issues:7Issues:0

maximalLearning

A tool to enable self-regulated learning

Language:JavaScriptStargazers:2Issues:2Issues:0
Language:HTMLLicense:MITStargazers:1Issues:1Issues:0

Self-Regulated-Learning

Group Project FHICT S64-2

Language:C#Stargazers:1Issues:2Issues:0

edu.SelfRegulatedLearning

Educational Self-Regulated Learning, i.e. watching video tutorials and replicating project for educational purposes.

course-teal-self-regulated-learning

This Moodle course is for Self-Regulated Learning. Self-Regulated Learning (SRL) refers to one's ability to understand and control one's learning behaviors. For the learner to do this, he or she must set goals, select the strategies to achieve the goals, and monitor progress towards the goals. In monitoring his or her progress, the learner can determine if a particular learning strategy is not working and he/she can modify the approach to mastering a skill. All of these activities, which can be customized to any content area, can help refine learners' attention to and confidence in learning and reinforcing specific habits, strategies, and skills. You can expect to complete this course in approximately 6 hours as you explore strategies for encouraging students to self-regulate their learning and for applying those strategies to the adult education context. You are asked to complete at least one of the assignments.

hle

Self-Regulated Learning Training System

Language:JavaScriptStargazers:1Issues:1Issues:0