| Fantastic resource - thanks, a16z! Do you accept pull requests? I'd like to make a suggestion for the software and services page: http://aiplaybook.a16z.com/docs/reference/software Also, I think there's an emerging category outside of MLaaS that focuses on ML/DL deployment (ops). Here's a quick intro: Seldon's mission is to help people predict and shape the future with machine learning. Our products increase efficiency and speed up the time to value for data scientists: Seldon Core - a machine learning platform that helps your data science team deploy models into production. It provides an open-source data science stack that runs within a Kubernetes Cluster. You can use Seldon to deploy machine learning and deep learning models into production on-premise or in the cloud (e.g. GCP, AWS, Azure). Seldon is framework agnostic, it supports models built with TensorFlow, Keras, Vowpal Wabbit, XGBoost, Gensim and any other model-building tool — it even supports models built with commercial tools and services where the model is exportable. Fork Seldon on Github: https://github.com/SeldonIO/seldon-server/ Seldon Deploy - in development - a machine learning deployment platform for data science teams. Features include workflows with approvals and audit trails, advanced experiments, continuous integration and model explanations. Seldon was part of the Barclays Techstars '16 and we’re working with customers in banking, technology and media sectors. Disclosure: I’m CEO at Seldon. |