#machine learning

Debugging Jupyter notebooks, consoles and source files

JupyterLab now has a visual debugger

For certain tasks, Jupyter users tend to switch to general-purpose IDEs. Therefore, the Jupyter project has decided to add a new feature that Jupyter users have been missing—a visual debugger in JupyterLab. Let’s take a closer look at the features of the debugging extension’s initial release.

Watch Dr. Yonit Hoffman's Machine Learning Conference session

Data to the Rescue! Predicting and Preventing Accidents at Sea

Accidents at sea happen all the time. Their costs – in terms of lives, money and environmental destruction – are huge. Wouldn’t it be great if they could be predicted and perhaps prevented? Dr. Yonit Hoffman’s Machine Learning Conference session discusses new ways of preventing sea accidents with the power of data science.

Atlas has a Python SDK, CLI & more on board

Deep learning platform Atlas is now open source

The deep learning company Dessa has open sourced Atlas, a deep learning platform. Though currently still in beta mode, it is designed to make running, evaluating and deploying deep learning projects easier. It works on macOS, Linux and Windows, and offers TensorBoard integration. Let’s take a closer look.

ML at the heart of business

3 global manufacturing brands at the forefront of AI and ML

How can machine learning and artificial intelligence change the landscape of manufacturing? According to reports by Deloitte and McKinsey, machine learning improves product quality and has the potential to double cash flow. Let’s take a look at three global manufacturers who are already on board.

TF Hub, TF Lite, a new certificate & more

A look at the TensorFlow ecosystem in 2020

TensorFlow Dev Summit 2020 took place last week and gave an overview of everything that’s been going on in the world of the machine learning library. While we have been covering TensorFlow, TensorFlow.js, and the recently open sourced TensorFlow Quantum, you may not yet have heard of TF Hub, TFX or TF Lite, so let’s see what they are all about.

TensorFlow.js survey by Google AI researchers

Web developers don’t need a math degree to get started with machine learning

Google AI researchers conducted a study among 645 users of TensorFlow.js, a framework for machine learning with JavaScript. The goal was to find out what motivates software developers to get started with machine learning, what they expect from ML frameworks and what challenges they face. Let’s see what the survey has brought to light.