This article delves into 5 popular deep learning frameworks, their applications and how they compare against each other. A must-read for everyone!
Interested in learning deep learning but don’t know where to start? We have put together a REALLY comprehensive learning path to get you started in 2019!
TensorFlow 2.0 will include eager execution as a central feature, support for more platforms and languages and removal of deprecated APIs.
Deep learning is coming up big in the industry these days. This article lists down what you need to know and learn, in a tidy and graphical format!
Studio.ml is an open source framework to simplify and accelerate model development. It is designed to help ML practioners speed up their experiments.
Overview The latest version of the popular TensorFlow Object Detection API has been released Updates include support for accelerating the training process thanks to …
Overview TensorFlow has launched an interactive in-browser platform called Seedbank Seedbank includes tons of machine learning examples and algorithms, including classification, unsupervised learning, NLP …
An artificial intelligence model managed to create a script, facial expressions, voice and select scenes to make an end-to-end movie. The neural network was built using TensorFlow, GANs and AWS. Check out the video inside!
Take a look at the top machine learning and data science GitHub repositories and Reddit discussions that were created in April, 2018.
Swift for TensorFlow was demo’d at the TensorFlow Conference last month and the code has now been open sourced on GitHub for the entire ML community.