Deep learning is always among the hottest topics and TensorFlow is one of the most popular frameworks out there. In this session, Khanderao Kand goes through some deep learning concepts in general and TensorFlow and Apache Spark in specific.
TensorFlow 1.9 is here! So what does this latest update mean for the popular machine learning project? For starters, there’s an improved tf.keras beginner’s guide. For everyone else, there’s eager execution, improved GRU and LSTM implementation, and gradient boosted trees estimators.
Joining companies such as eBay and Google, Twitter now uses TensorFlow as its machine learning framework. TensorFlow continues to be a fan favorite in the framework wars and it’s no wonder why more and more companies are adopting the technology.
It’s time to take a look at the hot list for the first quarter of 2018. Blockchain and Tensorflow lead the way, but there are some surprises further down the list. Who’s in, who’s out, and what should freelancers focus their energies on?
Get your bags packed, it’s time to migrate your machine learning models from TensorFlow into Deeplearning4j. This trip is a lot easier than you’d think, but there are still some pitfalls for the unwary.
Google’s machine learning framework TensorFlow is on the rise. We spoke to Christoph Henkelmann at ML Conference 2017 about its benefits in the enterprise and the reasons for using Java in this context. Furthermore, we talked about new trends in the world of machine learning.
TensorFlow 1.7 has just arrived. We take a look at one of the cool new features in the latest release: full integration for TensorRT! What does that mean for our favorite machine learning project? Faster performances, for one thing.
If you want to stay up-to-date on the hottest projects that everyone is talking about, you should start by bookmarking GitHub Trending — a list of trending repositories based on the number of stars they receive. This month, Flutter is the second most starred repository; could it have something to do with its first beta release? *cough*rhetorical question*cough*
Every year, Stack Overflow asks the developer community about everything from their favorite technologies to their job preferences. As always, we focus on the most popular technologies but we also skim through the most dreaded languages, libraries, frameworks and tools.
The internet’s favorite open source machine learning project is back with another update. What’s in TensorFlow 1.6? We take a look at some of the major features and improvements, bug fixes, breaking changes, and other issues.
TensorFlow, the internet’s most popular machine learning project, is back. What does this latest update bring to our favorite platform for ML? TensorFlow’s newest features include updates for Eager Execution, TensorFlow Lite, and more!
The most popular machine learning project becomes even more mobile-friendly with the introduction of TensorFlow Lite. Designed to be lightweight, cross-platform, and fast, this makes it even easier for machine learning models to be deployed on mobile or embedded devices.
TensorFlow 1.4 is here! The latest update to one of the most popular open source machine learning projects boasts big changes, new features, and even a couple of bug fixes.