Microsoft announces SQLServer update for mssql-cli, ENAS-PyTorch, NumPy v1.14.1 released, and more in today’s top stories around machine learning, deep learning,and data science news.
1. Microsoft announces SQLServer update for mssql-cli
Microsoft announced a new update for its mssql-cli, which is a new and interactive command line query tool for SQL Server. Mssql-cli is an open source tool that works cross-platform and is part of the dbcli community. In this v1.0.0, the feature highlights are the special commands.
Microsoft in its blog states that these special commands make various executions easier. They are shortcuts to perform common tasks and queries. All special commands start with a backslash (), and one can use the built-in IntelliSense to see a list of special commands that they can use.
Read more at SQL Server Blog.
2. ENAS-PyTorch: A PyTorch implementation of “Efficient Neural Architecture Search via Parameters Sharing”
Introducing ENAS-PyTorch, a PyTorch implementation of “Efficient Neural Architecture Search via Parameters Sharing. ENAS reduce the computational requirement (GPU-hours) of Neural Architecture Search (NAS) by 1000x. This is done via parameter sharing between models that are subgraphs within a large computational graph.
To know more in detail, visit the GitHub repository.
3. NumPy v1.14.1 released
NumPy version 1.14.1 released. This is a bugfix release for some problems reported following the 1.14.0 release.
The major problems fixed include:
- Problems with the new array printing, particularly the printing of complex values.
- Problems with np.einsum due to the new optimized=True default. Some fixes for optimization have been applied and optimize=False is now the default.
- The sort order in np.unique when axis=<some-number> will now always be lexicographic in the subarray elements. In previous NumPy versions there was an optimization that could result in sorting the subarrays as unsigned byte strings.
- The change in 1.14.0 that multi-field indexing of structured arrays returns a view instead of a copy has been reverted but remains on track for NumPy 1.15.
To know more, read NumPy’s release notes.
4. Feature Labs Launches Software Solutions to Automate Feature Engineering for Machine Learning and AI Applications
Feature Labs, Inc., launched a set of tools to aid data scientists build machine learning algorithms more quickly. As stated by Max Kanter, CEO and founder of Feature Labs, the company plans to automate ‘feature engineering’, a time consuming and manual process for data scientists.
Feature Labs uses “Deep Feature Synthesis” to automatically create features from raw relational and transactional datasets. Max Kanter also said,“Feature Labs is unique because we automate feature engineering, which is the process of using domain knowledge to extract new variables from raw data that make machine learning algorithms work.”
Read more about this news in detail on Feature Labs’ official website.
5. SentryOne Releases Version 18.1 with Enhanced Support of SSAS Tabular
SentryOne released Version 18.1of its SentryOne Platform. This updated version has an enhanced support of SSAS Tabular in BI Sentry. Bi Sentry is the complete performance monitoring, diagnosis, and optimization solution for SQL Server Analysis Services (SSAS).
Jason Hall, SentryOne Vice President of Product, said, “This update also introduces general performance enhancements to the SentryOne client, and additional performance enhancements to our APS and Azure SQL DW products.”
For a more detailed information read the official press release.