In Part 3 of this mini-series on TensorFlow high-level APIs, TensorFlow Engineering Manager Karmel Allison runs us through different scenarios using TensorFlow’s high-level APIs.

With the TensorFlow model defined, Karmel discusses how to establish layer architecture, and compile the model, adding the optimizer, loss, and metrics that we are interested in. She also runs through the various steps taken to refine the model.

At GDG DevFest Ukraine 2018, Asim Hussain talks about the many exciting things are happening with AI, from which, until recently, JavaScript developers were mostly shut out. However, things are changing. If you can do npm install @tensorflow/tfjs or make an API call, you can now do AI.

In this fast-paced talk, he’ll open your mind to what’s possible by demoing several AI-powered JavaScript apps and show you how I built them using either TensorFlow.js or easy to use AI-powered APIs.

Best of all, you won’t need a PhD in Math or years of experience. You just need imagination and the willingness to try.

In this talk from the most recent O’Reilly AI Conference, Laurence Moroney from Google talked about Machine Learning, AI, Deep Learning and more, and how they fit the programmers toolkit. He introduced what it’s all about, cutting through the hype, to show the opportunities that are available in Machine Learning. He also introduced TensorFlow, and how it’s a framework that’s designed to make Machine Learning easy and accessible, and how intelligent apps that use ML can run in a variety of places including mobile, web and IoT.

TensorFlow Engineering Manager Karmel Allison walks through different scenarios using TensorFlow’s high-level APIs.

Building a ML model takes a lot of time, effort, and often involves multiple stages. Fortunately, TensorFlow high-level APIs aim to help you along with each stage, from the start of your idea, to training and serving large scale applications. Watch to discover the key steps in developing machine learning models, where TensorFlow comes in for each step, and lastly how to prepare and load your data!

Find out how does TensorFlow applies to nuclear physics in this episode of TensorFlow Meets, as Laurence chats with TensorFlow Software Engineer, Ian Langmore.

Learn about power generated from nuclear fusion, new plasma generator machines, and how TensorFlow is helping with plasma measurement. Subscribe to the TensorFlow channel to stay up to date with Google’s open source machine learning platform.

Josh Gordon sits down with J.J. Allaire, the founder of RStudio. They discuss TensorFlow and Keras support in R, and the educational resources available for R developers new to deep learning. Learn more about the R interface to Keras, TensorFlow Estimators, and the Core TensorFlow API that allows the R community access to many machine learning tools.

TensorFlow Meets Chip Huyen (@chipro), author and instructor of the TensorFlow for Deep Learning class at Stanford University: https://goo.gl/rNb6PW. In this video, she discusses the class, her journey from writing travel stories, to studying computer science, to now teaching students about deep learning at Stanford University!