Like all machine learning algorithms, Decision Forests have hyper-parameters. The default values of those parameters give good results, but, if you really want the best possible results for your model, you need to "tune" those parameters. TF-DF makes it easy to tune parameters. Starting with TF-DF 1.0, you can use the pre-configured hyper-parameter tuning search space. Check the hyper-parameter tuning tutorial for more details.

We've started planning the future of TensorFlow! In this article, we'd like to share our vision. Since then, thanks to thousands of open-source contributors and our incredible community of Google Developer Experts, community organizers, researchers, and educators around the globe, TensorFlow has come to define its category. Today, TensorFlow is the most-used machine learning platform, adopted by millions of developers. It has brought machine learning to the mobile ecosystem: TFLite now runs on four billion devices (maybe on yours, too!).

I've often wondered why anonymity drives people to say things that they'd never dare say in person, and it's unfortunate that comment sections for videos and articles are so often toxic! If you're interested in content moderation, you can use machine learning to help detect toxic posts which you consider for removal. Machine learning is a powerful tool for all sorts of natural language-processing tasks, including translation, sentiment analysis, and predictive text. But perhaps it feels outside the scope of your work. After all, when you're building a website in JavaScript, you don't have time to collect and validate data, train a model using Python, and then implement some backend in Python on which to run said model.