JAX vs Tensorflow vs Pytorch: Building a Variational Autoencoder (VAE)
A side-by-side comparison of JAX, Tensorflow and Pytorch while developing and training a Variational Autoencoder from scratch
A side-by-side comparison of JAX, Tensorflow and Pytorch while developing and training a Variational Autoencoder from scratch
Table of Contents Introduction to Autoencoders What Are Autoencoders? How Autoencoders Achieve High-Quality Reconstructions? Revisiting the Story Types of Autoencoder Vanilla Autoencoder Convolutional Autoencoder (CAE) Denoising Autoencoder Sparse Autoencoder Variational Autoencoder (VAE) Sequence-to-Sequence Autoencoder What Are the Applications of Autoencoders?…
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Table of Contents What Is Keras Core? Configuring Your Development Environment Let’s Talk about Keras! Going Beyond with Keras Core The Power of Keras Core: Expanding Your Deep Learning Horizons Show Me Some Code JAX Harnessing model.fit() Imports and Setup…
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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 Matthew Seal who talked about the work he has been doing with Jupyter and Nteract. Matthew also discussed a particular topic: common Jupyter tools and their adoption for various use cases in the wild.
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.