Google’s Cloud AutoML, Uber AI Labs’ Neuroevolution and Safemutation, G Suite’s new security center, visual tools for Azure data factory, and more in today’s top stories around machine learning, and data science news.
1. Google’s Cloud AutoML lets businesses train Machine Learning models without having to code.
Google has launched their Cloud AutoML service to make machine learning accessible to all enterprises. This service will help businesses with limited ML expertise start building their own high-quality custom models by using advanced techniques like learning2learn and transfer learning from Google. Here are a few advantages:
- Cloud AutoML provides businesses with a more accurate model even if the business has limited machine learning expertise.
- It provides a faster turnaround time to production-ready models.
- It is easy to use with a simple graphical user interface for specifying data.
Their, first Cloud AutoML release would be Cloud AutoML Vision, a service for creating custom ML models for image recognition. With Vision, businesses can easily upload images, train and manage models, and then deploy them directly on Google Cloud.
2. Uber AI Labs open sources neuroevolution and safe mutation implementations to solve reinforcement learning problems
Uber AI labs announced today that it is open sourcing two implementations, namely Neuroevolution and safemutations. These will make it easy for researchers to train their deep neural networks in order to solve reinforcement learning problems.
Neuroevolution introduces a Deep genetic algorithm(GA), which involves a simple parallelization trick that allows training deep neural networks with GAs. These GAs are surprisingly competitive with popular algorithms for deep reinforcement learning problems, such as DQN, A3C, and ES, especially in the challenging Atari domain. Also, interesting algorithms developed in the neuroevolution community can now immediately be tested with deep neural networks, by showing that a Deep GA-powered novelty search can solve a deceptive Atari-scale game. To know more about this in detail, read the research paper.
Safe mutation (SM) operators aim to find a degree of change within the mutation operator itself that does not alter network behavior too much but still facilitates exploration. The safe mutation through gradients (SM-G) operator increases the ability of a simple genetic algorithm-based neuroevolution method to find solutions in high-dimensional domains. These domains are those which require deep or recurrent neural networks or domains that require processing raw pixels. By improving the ability to evolve deep neural networks, this new safer approach to mutation expands the scope of domains amenable to neuroevolution. To read more on this, visit the research paper.
3. G Suite launches a new security center with unified dashboard, analytics, & recommendations
Google has introduced a new security center for G Suite. This tool brings together security analytics, actionable insights, and best practice recommendations from Google for protecting an organization and its data and users. It consists of three main parts.
- A unified dashboard, which will get insights into suspicious device activity and visibility into how spam and malware are targeting users. It will also provide metrics to demonstrate security effectiveness.
- Security analytics, where admins can examine analytics to flag threats.
- Security health, which reduces risk by providing security health recommendations. It analyzes existing security metrics and gives customized advice to secure users and data.
4. Microsoft announces visual tools for Azure Data Factory v2
Microsoft has added new visual tools for Azure Data Factory (ADF) v2. ADF v2 public preview was announced at Microsoft Ignite on Sep 25, 2017.
ADF visual tools provide a simple and intuitive code free interface to drag and drop activities on a pipeline canvas, perform test runs, debug iteratively, and deploy and monitor pipeline runs. It also provides guided tours on how to use the enabled visual authoring & monitoring features including support for all control flow activities running on Azure computes. Moreover, users can validate their pipelines to know about missed property configurations or incorrect configurations. More details are available on their official blog.
5. A new release of SQL Operations Studio is now available
Microsoft has announced the January release of their SQL Operations Studio. SQL Operations Studio was announced for public preview at Connect () conference in November 2017. Some major repo updates and feature releases include:
- HotExit feature is now enabled to automatically reopen unsaved files.
- Saved connections can now be accessed from Connection Dialog.
- SQL editor tab color now matches the Server Group color.
- Run Current Query command fixed.
- Broken pinned Windows Start Menu icon fixed.
- Saved Server connections are available in the Connection Dialog.
- Drag-and-drop breaking scripting bug is fixed.
- Missing Azure Account branding icon is added.
For a complete list of updates, refer to the changelog.