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As 2020 begins, there has been limited clouddata science announcements so I put together some predictions. Here are 3 things I believe will happen in 2020. Cloud Collaboration. I think we are going to see more interoperability between the major cloud providers. It even does some feature engineer.
It was an exciting clouddata science week. Microsoft DP-100 Certification Updated – The Microsoft Data Scientist certification exam has been updated to cover the latest Azure Machine Learning tools. It is nice to know the level of abstraction for various ML tools in Google Cloud. Courses/Learning.
The CloudData Science world is keeping busy. Azure HDInsight now supports Apache analytics projects This announcement includes Spark, Hadoop, and Kafka. The frameworks in Azure will now have better security, performance, and monitoring. AWS DeepRacer 2020 Season is underway This looks to be a fun project.
Welcome to CloudData Science 8. This weeks news includes information about AWS working with Azure, time-series, detecting text in videos and more. Amazon Redshift now supports Authentication with Microsoft Azure AD Redshift, a data warehouse, from Amazon now integrates with Azure Active Directory for login.
Welcome to CloudData Science 5. There were not as many announcements as last week in CloudData Science 4 , but quantity is not what is important. Mastering Azure Machine Learning is coming soon – This course will cover how to use Azure Machine Learning to solve business problems. Courses / Learning.
Lots of announcements this week, so without delay, let’s get right to CloudData Science 9. Google Announces Cloud SQL for Microsoft SQL Server Google’s Cloud SQL now supports SQL Server in addition to PostgreSQL and MySQL Google Opens a new Cloud Region Located in Salt Lake City, Utah, it is named us-west3.
2020 is now in full swing and the announcements are starting to show up. Google Releases a tool for Automated Exploratory Data Analysis Exploring data is one of the first activities a data scientist performs after getting access to the data. It focuses on using AWS products to solve data science problems.
This is a great talk for data scientists and managers of technology teams. If you do data science in 2020 or beyond, there is a good chance the cloud will be involved.
Snowflake is a cloud computing–based datacloud company that provides data warehousing services that are far more scalable and flexible than traditional data warehousing products. In a perfect world, Microsoft would have clients push even more storage and compute to its Azure Synapse platform.
At DataRobot, we also know that business apps can only enable our customers to nimbly act on insights when the data driving the models can be trusted. During the pandemic, we witnessed mature machine learning models failing overnight because models trained on 2019 data didn’t know what to do with 2020 market conditions.
This is a great talk for data scientists and managers of technology teams. If you do data science in 2020 or beyond, there is a good chance the cloud will be involved.
EO data is not yet a commodity and neither is environmental information, which has led to a fragmented data space defined by a seemingly endless production of new tools and services that can’t interoperate and aren’t accessible by people outside of the deep tech community ( read more ). Licensing FAIR data for reuse. Marujo, R.
Co-location data centers: These are data centers that are owned and operated by third-party providers and are used to house the IT equipment of multiple organizations. Edge data centers: These are data centers that are located closer to the edge of the network, where data is generated and consumed, rather than in central locations.
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