Embeddings are not just for use in natural language processing. Here we apply embeddings to a common task in collaborative filtering – predicting user ratings – and on our way, strive for a better understanding of what an embedding layer really does.
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.
In this episode of Open Source Directions we were joined by Jeff Bezanson and Katie Hyatt who talk about the work they have been doing with Julia. Julia is a programming language that was designed from the beginning for high performance. It programs compile to native code for multiple platforms via LLVM. Julia is dynamically typed, feels like a scripting language, and has good support for interactive use.
Table of Contents CycleGAN: Unpaired Image-to-Image Translation (Part 3) Configuring Your Development Environment Need Help Configuring Your Development Environment? Project Structure Implementing CycleGAN Training Implementing Training Callback Implementing Data Pipeline and Model Training Perform Image-to-Image Translation Summary Citation Information CycleGAN:…
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In this episode, I was fortunate enough to speak with Peter Wang, the CEO of Anaconda. Anaconda is a distribution for the Python and R programming languages for scientific computing. It’s recognized as the heart of the open source data science community.
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.
