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.
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.
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.
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.
It’s not a secret that deep learning already made a revolution in several perception fields as vision, language and speech understanding and keeps pushing the frontiers. Take a tour of the final frontier for time series analysis in this advanced development session from the Machine Learning Conference.
Demucs is a new research project by Facebook AI. It is designed to separate musical tracks into different instruments or vocals, similar to how a human can detect the specific instruments, and solve the problems of existing approaches. In the long run, Demucs could be applied to other AI tasks as well.
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.
The TensorFlow developers have been keeping busy this week: Not only has the first release candidate for TensorFlow 2.2 arrived, but we can now also welcome the very first release of TensorFlow Quantum. Let’s see what has been happening in the world of Google’s machine learning framework.
Developers and programmers can be notoriously difficult to shop for, especially if they already have the requisite collection of mugs and t-shirts. What if you wanted to buy something special? Something that combines their passion with their hobbies? Well have no fear, we’ve got you covered with this great gift for developers.
Kubeflow, the open source machine learning solution for Kubernetes, reached a new milestone. Version 1.0 graduates several core applications for developing, training, and deploying models on Kubernetes. Have a look at what applications have been graduated, and how Kubeflow can help you create and deploy Jupyter notebooks and more.
What are autoencoders and how can you use them in your machine learning projects? In this session from the Machine Learning Conference, Christoph Henkelmann will teach you all about the basics of autoencoders, including different varieties, how to use them, and what they are good for.
Node.js is one of the most popular frameworks for writing server side applications now, and machine learning is rapidly gaining popularity. More and more problems are being solved by using machine learning tools. The use of machine learning solutions is spreading, and it is not limited to researchers.