NLP Cloud
spaCy
Amazon Comprehend
Google Cloud Natural Language API
Polyglot NLP
TextBlob
OpenNLP
Hugging Face
Apple Machine Learning Journal
Amazon Machine Learning
Machine Learning Playground
Lobe
A.I. Experiments by Google
ML5.js
mlblocks
ML Showcase
NLP Cloud serves high performance pre-trained or custom models for NER, sentiment-analysis, classification, summarization, dialogue summarization, paraphrasing, intent classification, product description and ad generation, chatbot, grammar and spelling correction, keywords and keyphrases extraction, text generation, question answering, machine translation, language detection, semantic similarity, tokenization, POS tagging, embeddings, and dependency parsing. It is ready for production, served through a REST API.
You can either use the NLP Cloud pre-trained models, fine-tune your own models, or deploy your own models.
NLP Cloud Apple Machine Learning JournalBased on our record, NLP Cloud should be more popular than Apple Machine Learning Journal. It has been mentiond 41 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
NLP Cloud (their Dolphin and Fine-tuned GPT-NeoX models). Source: 11 months ago
I am using NLP Cloud more and more and have not seen such quality drop with their service. Source: 12 months ago
You have NLP Cloud which is a nice and comprehensive OpenAI competitor. Source: 12 months ago
You should try NLP Cloud, they don't censor their text generation models: https://nlpcloud.com/home/playground. Source: 12 months ago
You can use NLP Cloud, as far as I know they don't ban anybody and don't filter NSFW. Source: 12 months ago
For your reference, Apple's pages for Machine Learning for Developers and for their research. The Apple Neural Engine was custom designed to work better with their proprietary machine learning programs -- and they've been opening up access to developers by extending support / compatibility for TensorFlow and PyTorch. They've also got CoreML, CreateML, and various APIs they are making to allow more use of their... Source: about 1 year ago
We even host annual poster sessions of those PhD intern’s work while at our company, and it’ll give you an idea of the caliber of work. It may not be as great as Nvidia, Stryker, Waymo, or Tesla (which are not part of MAANG but I believe are far more ahead in CV), but it’s worth of considering. Source: about 1 year ago
They have something for ML: https://machinelearning.apple.com. - Source: Hacker News / about 2 years ago
They're more subtle about it, I think. https://machinelearning.apple.com/ Some of the papers are pretty good. I don't disagree with your sentiment in aggregate, though. Source: about 2 years ago
Siri is not where it needs to be because Apple refuses to mine user data to enrich it. They also are very hesitant to allow researchers to publish their breakthroughs which makes recruitment very hard. Although this is changing https://machinelearning.apple.com/. - Source: Hacker News / about 2 years ago
spaCy - spaCy is a library for advanced natural language processing in Python and Cython.
Amazon Machine Learning - Machine learning made easy for developers of any skill level
Amazon Comprehend - Discover insights and relationships in text
Machine Learning Playground - Breathtaking visuals for learning ML techniques.
Google Cloud Natural Language API - Natural language API using Google machine learning
Lobe - Visual tool for building custom deep learning models