TensorFlow Lite Task Library is a set of powerful and easy-to-use task-specific APIs for app developers to create ML experiences with TensorFlow Lite. Inference can be done within just 5 lines of code!

The Incredible PyTorch: a curated list of tutorials, papers, projects, communities and more relating to PyTorch. - GitHub - ritchieng/the-incredible-pytorch: The Incredible PyTorch: a curated list...

Machine learning models have hyperparameters that you must set in order to customize the model to your dataset. Often the general effects of hyperparameters on a model are known, but how to best set a hyperparameter and combinations of interacting hyperparameters…

An introduction to the open-sourced end-to-end solution for TFLite on-device recommendations, that are personalized, low-latency, high-quality and privacy preserving.

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❤️ Their report on this paper is available here: https://app.wandb.ai/authors/rewrite-gan/reports/An-Overview-Rewriting-a-Deep-Generative-Model--VmlldzoyMzgyNTU…

This blog introduces the end-to-end support for NLP tasks based on TensorFlow Lite. It describes new features including pre-trained NLP models, model creation, conversion and deployment on edge devices.

Posted by Andrew Carroll, Product Lead and Pi-Chuan Chang, Technical Lead, Google Health Sequencing genomes involves sampling short pieces of the D...

(ICML 2021) Implementation for S2SD - Simultaneous Similarity-based Self-Distillation for Deep Metric Learning. Paper Link: https://arxiv.org/abs/2009.08348 - GitHub - MLforHealth/S2SD: (ICML 2021)...

Many computationally expensive tasks for machine learning can be made parallel by splitting the work across multiple CPU cores, referred to as multi-core processing. Common machine learning tasks that can be made parallel include training models like ensembles…

Researchers at Microsoft Semantic Machines are taking a new approach to conversational AI—modeling dialogues with compositional dataflow graphs. Learn how the framework supports flexible, open-ended conversations, and explore the dataset and leaderboard.

Is FashionMNIST, a dataset of images of clothing items labeled by category, more similar to MNIST or to USPS, both of which are classification datasets of handwritten digits? This is a pretty hard question to answer, but the solution could have an impact…

PyTorch implementation of DCGAN, WGAN-GP and SNGAN. - GitHub - w86763777/pytorch-gan-collections: PyTorch implementation of DCGAN, WGAN-GP and SNGAN.

Data that is updated in real-time requires additional handling and special care to prepare it for machine learning models. The important Python library, Pandas, can be used for most of this work, and this tutorial guides you through this process for analyzing…

Подборка проверенных источников о data science: блоги, телеграм-каналы, twitter, СМИ. Для специалистов и всех тех, кто хочет разобраться, как устроена наука о данных

Teaching computers to understand how humans write and speak, known as natural language processing or NLP, is one of the oldest challenges in AI research. There has been…

In this article, we'll perform facial detection on images and a live webcam using Python and OpenCV.

PyTorch helps AstraZeneca apply advanced machine learning to drug discovery.