Deep learning based facial detector for Python coming with facial landmarks.
An article by Cavin on Deep Markets discussing machine-generated content and creativity. It describes technology as leverage over creation: writing, the printing press, the internet, digital tools and machine learning. It also covers synthetic text from large language models such as OpenAI's GPT-3, published in summer 2020.
Text Mining with R: A Tidy Approach is a website for a guide to text analysis within the tidy data framework, using the tidytext package and other tidy tools. It is written by Julia Silge and David Robinson and licensed under Creative Commons Attribution-NonCommercial-ShareAlike 3.0 United States License.
Vellum is a personal AI assistant available locally or in the cloud, with long-term memory across conversations. It can send emails, manage calendars, browse the web, create slides, write code, run research, and execute recurring background tasks. It offers fine-grained permissions requiring approval for high-stakes actions until marked trusted. Two plans exist: Base (free) and Pro packages Mighty, Super, and Ultra.
Feast is an end-to-end open source feature store for machine learning. It allows teams to define, manage, discover, and serve features, delivering structured data to AI and LLM applications during training and inference. Documented use cases include real-time recommendations, fraud detection, risk scoring, and customer segmentation.
The AI Safety Summit 2023 is a global event held on 1 and 2 November at Bletchley Park, Buckinghamshire. It brings together international governments, AI companies, civil society groups and researchers to consider AI risks, especially at the frontier of development, and discuss mitigation through internationally coordinated action.
Gensim is a free open-source Python library for topic modelling and semantic NLP. It trains large-scale semantic models, represents text as semantic vectors and finds semantically related documents. The site describes streaming of arbitrarily large corpora, platform independence, and pretrained models and corpora published by the community.
Community notes
Be the first to share how this project worked for you.
Sign in with a verified account to leave a review or join the discussion.
Sign in to reviewKeep exploring
An article by Cavin on Deep Markets discussing machine-generated content and creativity. It describes technology as leverage over creation: writing, the printing press, the internet, digital tools and machine learning. It also covers synthetic text from large language models such as OpenAI's GPT-3, published in summer 2020.
Text Mining with R: A Tidy Approach is a website for a guide to text analysis within the tidy data framework, using the tidytext package and other tidy tools. It is written by Julia Silge and David Robinson and licensed under Creative Commons Attribution-NonCommercial-ShareAlike 3.0 United States License.
Vellum is a personal AI assistant available locally or in the cloud, with long-term memory across conversations. It can send emails, manage calendars, browse the web, create slides, write code, run research, and execute recurring background tasks. It offers fine-grained permissions requiring approval for high-stakes actions until marked trusted. Two plans exist: Base (free) and Pro packages Mighty, Super, and Ultra.
Feast is an end-to-end open source feature store for machine learning. It allows teams to define, manage, discover, and serve features, delivering structured data to AI and LLM applications during training and inference. Documented use cases include real-time recommendations, fraud detection, risk scoring, and customer segmentation.
The AI Safety Summit 2023 is a global event held on 1 and 2 November at Bletchley Park, Buckinghamshire. It brings together international governments, AI companies, civil society groups and researchers to consider AI risks, especially at the frontier of development, and discuss mitigation through internationally coordinated action.
Gensim is a free open-source Python library for topic modelling and semantic NLP. It trains large-scale semantic models, represents text as semantic vectors and finds semantically related documents. The site describes streaming of arbitrarily large corpora, platform independence, and pretrained models and corpora published by the community.
