Will Kwan was told he wasn’t beautiful enough to be an Instagram model so he used a generative adversarial network to generate some beautiful Instagram people to pose for me.

Code:

Microsoft for Startups shares this highlight reel from the Spring MLADS conference.

In case you’re not familiar with MLADS, check out Data Driven’s coverage of the most recent one.

Twice a year, Microsoft assembles over 4,000 of our top data scientists and engineers for a two day internal conference to explore the state of the art around machine learning and data science.

Earlier this year, 30 leading startups who are active in the Microsoft for Startups program came to showcase their solutions and engage directly with the engineering teams.

TensorFlow 2.0 is all about ease of use, and there has never been a better time to get started.

In this talk, learn about model-building styles for beginners and experts, including the Sequential, Functional, and Subclassing APIs.

We will share complete, end-to-end code examples in each style, covering topics from “Hello World” all the way up to advanced examples. At the end, we will point you to educational resources you can use to learn more.

Presented by: Josh Gordon

View the website → https://goo.gle/36smBfW

O’Reilly and TensorFlow teamed up to present the first TensorFlow World last week.

It brought together the growing TensorFlow community to learn from each other and explore new ideas, techniques, and approaches in deep and machine learning.

Presenters in the keynote:

  • Jeff Dean, Google
  • Megan Kacholia, Google
  • Frederick Reiss, IBM
  • Theodore Summe, Twitter
  • Craig Wiley, Google
  • Kemal El Moujahid, Google

Samuel Arzt shows off a project where an AI learns to park a car in a parking lot in a 3D physics simulation.

The simulation was implemented using Unity’s ML-Agents framework (https://unity3d.com/machine-learning).

From the video description:

The AI consists of a deep Neural Network with 3 hidden layers of 128 neurons each. It is trained with the Proximal Policy Optimization (PPO) algorithm, which is a Reinforcement Learning approach.

The TensorFlow team has been on a journey to make the training, deployment, managing, and scaling of machine learning Machine Learning models as easy as possible.

TensorFlow 2.0 provides a comprehensive ecosystem of tools for developers, enterprises, and researchers who want to push the state-of-the-art machine learning and build scalable ML-powered applications.

This video is also subtitled in Chinese, Indonesian, Italian, Japanese, Korean, Portuguese, and Spanish.


Watch more

Coding TensorFlow → https://goo.gle/2Y43cN4