OpenBot leverages smartphones as brains for low-cost robots. We have designed a small electric vehicle that costs about $50 and serves as a robot body. Our software stack for Android smartphones supports advanced robotics workloads such as person following and real-time autonomous navigation.

#java, #jvm, #android, #robot, #robotics, #education, #research

🤗 multilingual datasets

- 611 datasets you can download in one line of python;
- 467 languages covered, 99 with at least 10 datasets;
- efficient pre-processing to free you from memory constraints;

https://github.com/huggingface/datasets

Rasa is a open source machine learning framework to automate text- and voice-based conversations: NLU, dialogue management, connect to Slack, Facebook, and more - Create chatbots and voice assistants.

#python, #nlp, #ml, #bots, #botkit, #wit, #conversational, #ai, #chatbot, #framework

Datasets

Datasets collected for network science, deep learning and general machine learning research.

Github: https://github.com/benedekrozemberczki/datasets

Paper: https://arxiv.org/abs/2101.03091v1

@ai_machinelearning_big_data

🦾 Robustness Gym is a Python evaluation toolkit for natural language processing.

Github: https://github.com/robustness-gym/robustness-gym

Paper: https://arxiv.org/abs/2101.04840v1

Project: https://robustnessgym.com/

@ai_machinelearning_big_data

LabML Neural Networks.

This is a collection of simple PyTorch implementations of neural networks and related algorithms.

These implementations are documented with explanations, and the website renders these as side-by-side formatted notes.

#python, #ml, #dl, #neural, #networks

TensorTrade is an open source Python framework for building, training, evaluating, and deploying robust trading algorithms using reinforcement learning. The framework focuses on being highly composable and extensible, to allow the system to scale from simple trading strategies on a single CPU, to complex investment strategies run on a distribution of HPC machines.

#python, #reinforcement, #learning

Hub is fastest unstructured dataset management for TensorFlow/PyTorch. Stream data real-time & version-control it.

Software 2.0 needs Data 2.0, and Hub delivers it. Most of the time Data Scientists/ML researchers work on data management and preprocessing instead of training models. With Hub, we are fixing this. We store your (even petabyte-scale) datasets as single numpy-like array on the cloud, so you can seamlessly access and work with it from any machine. Hub makes any data type (images, text files, audio, or video) stored in cloud usable as fast as if it were stored on premise. With same dataset view, your team can always be in sync.

#python, #tensorflow, #pytorch, #training, #data, #science, #ml, #ai, #dl, #distributed, #dataset, #mlops

2020 in ML and NLP publications

By conferences, countries, companies, universities and most productive scientists:
https://www.marekrei.com/blog/ml-and-nlp-publications-in-2020/

Deep Learning with PyTorch Quick Start Guide

@datascienceiot

PySyft is a Python library for secure and private Deep Learning. PySyft decouples private data from model training, using Federated Learning, Differential Privacy, and Encrypted Computation (like Multi-Party Computation (MPC) and Homomorphic Encryption (HE) within the main Deep Learning frameworks like PyTorch and TensorFlow.

#python #cryptography #privacy #deeplearning #pytorch #secure #computation