Semi-supervised learning (SSL) unlocks value in your unlabeled data, but it can be difficult to implement. Masterful can fully automate model training and apply SSL, but it also allows users to easily use SSL with their existing training code. We call this Simple SSL, and the benefits are less labeling and a more accurate model. In this post we'll show you how to try it.
Today we’re making a big leap forward in enabling new applications and insights for every enterprise that uses visual data. We’re releasing the next version of Masterful, the platform that automates model development for computer vision. Masterful now includes a low-code interface that enables developers to build models faster than ever before. Using a simple command-line interface (CLI), any developer can build production-grade models without needing to write code in TensorFlow or PyTorch. Our low-code interface also opens up CV development to an even wider universe of developers!
Once your training runs become material in terms of wall-clock time and hardware budget, it's time to look at improving your batch size. If your batch size is too small, your training runs are taking longer than necessary and you are wasting money. And if your batch size is too large, you are training with more expensive hardware than you need.
We're thrilled to announce that the Masterful AutoML platform is now available on the Python Package Index for everyone to use. Installation is as easy as pip install masterful. You get the full power of our deep learning platform to train your models to peak performance without manual tuning. With Masterful, developers can focus on solving problems with ML instead of wasting time and brain cells running endless training experiments.