Object detection (the act of classifying and localizing multiple objects in a scene) is one of the more difficult, but very relevant in practice deep learning tasks. We’ll build up to it in several posts. Here we start with the simpler tasks of naming and locating a single object.
In this episode of Open Source Directions, we were joined by Thomas Wiecki once again who talked about the work being done with PyMC. PyMC3 is a Python package for Bayesian statistical modeling and Probabilistic Machine Learning focusing on advanced Markov chain Monte Carlo (MCMC) and variational inference (VI) algorithms. Its flexibility and extensibility make it applicable to a large suite of problems.
With the rapid advance in NLP models we have outpaced out ability to measure just how good they are at human level language tasks. We need better NLP datasets now more than ever to both evaluate how good these models are and to be able to tweak them for out own business domains.
In this episode, we have an engaging and very entertaining discussion with Jono Bacon, the founder of Jono Bacon Consulting. Jono was Director of Community at notable companies such as Github, Canonical, and XPRIZE. He is one of the top (if not the top) experts in the world when it comes to building strong communities.
Fortran is a compiled language which means that once written, the source code must be passed through a compiler to produce a machine executable that can be run.
In this episode of Open Source Directions, we were joined by Fabian Franz who talked about the work being done with Drupal. Drupal is a content management software. It’s used to make many of the websites and applications you use every day. Drupal has great standard features, like easy content authoring, reliable performance, and excellent security. But what sets it apart is its flexibility; modularity is one of its core principles. Its tools help you build the versatile, structured content that dynamic web experiences need.
