Machine learning platforms
Enterprises need to make smart investments in machine learning platforms. With a range of features and price tags, making the right choice can seem like a daunting task. Discover machine learning platform comparison content, information on getting started with machine learning algorithms and best practices to gain the most from projects.
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We designed this expert guide to help you better understand all of the considerations for building and maintaining the infrastructure and engine that support the initiatives. Plus, learn about the products and players, like Amazon, Google, IBM, and 16 more to help you make the best buying decision.
Machine learning platforms News
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April 17, 2019
17
Apr'19
Real-time machine learning with Splice Machine's ML Manager
Splice Machine's AI management software ML Manager, shown at Spark + AI Summit 2019, enables users to update their machine learning models with up-to-date data from varied sources.
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April 10, 2019
10
Apr'19
Cloud AutoML, BigQuery ML upgrades expand Google stake in ML
Google introduced a raft of updates to its cloud-based machine learning and AI products, including expanded capabilities for its AutoML and BigQuery ML tools.
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April 08, 2019
08
Apr'19
Google's BigQuery ML needs big changes to compete
On the eve of Google Cloud Next '19, experts assess the impact of Google's BigQuery ML since its release and their hopes for the automated machine learning tool's future.
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April 02, 2019
02
Apr'19
$1 billion SAS AI investment recharges vendor's mission
SAS' new AI initiative includes a $1 billion investment and partnership with AI chip vendor Nvidia. The goal is to bring advanced AI tech to end users.
Machine learning platforms Get Started
Bring yourself up to speed with our introductory content
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Enterprise AI collaboration tools take tips from dating apps
Enterprise AI collaboration is turning to an unlikely source for inspiration: dating apps that have long used machine-learning based personalization and communication. Continue Reading
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Data science and machine learning platforms advance analytics
Data science platforms include a variety of technologies for machine learning and other advanced analytics uses. This handbook examines them and how they can be used. Continue Reading
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Windows Server 2019 features admins should explore
This slideshow of Windows Server 2019 features highlights some of its key additions built to bring more flexibility and reliability to the enterprise. Continue Reading
Evaluate Machine learning platforms Vendors & Products
Weigh the pros and cons of technologies, products and projects you are considering.
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Federated deep learning offers new approach to model training
Training deep learning models puts a massive strain on enterprise infrastructure, but federated learning, which trains models on endpoint devices, could lessen some of the demand. Continue Reading
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How to address the hidden risks of algorithmic decision making
From biased customer interactions to harmful treatment recommendations, some risks of automated decisions have yet to be resolved. A Wharton School professor has a way out. Continue Reading
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Data preparation for machine learning still requires humans
Looking to AI to automate more of your processes? Don't overlook the labor that's still needed to prepare data for training machine learning and AI algorithms. Continue Reading
Manage Machine learning platforms
Learn to apply best practices and optimize your operations.
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Data scientists urged to take AI security threats more seriously
AI security hasn't been the top concern of most data scientists using machine learning. But as these systems move closer to the core of the business, security is becoming critical. Continue Reading
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Enterprise AI tools help cultivate better business health
AI technologies can give companies a business boost, enough so that the number of available jobs for humans may increase instead of declining due to more automation. Continue Reading
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Combat algorithm bias with these software test pointers
As AI penetrates all kinds of software, it's imperative that testers devise a plan to verify predictive results. Put QA professionals on task to root out AI bias. Continue Reading
Problem Solve Machine learning platforms Issues
We’ve gathered up expert advice and tips from professionals like you so that the answers you need are always available.
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March Madness analytics, AI help data scientist fill bracket
To create his March Madness bracket predictions, the head of data science at DataRobot uses a host of machine learning algorithms and some predictive analytics. Continue Reading
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Hospitals battle duplicate medical records with technology
See how IT executives at two healthcare organizations weed out patient identification errors related to duplicate medical records -- a significant problem, according to research. Continue Reading
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Convert unstructured data to structured data with machine learning
With access to powerful compute power and advances in machine learning, unstructured data is becoming easier and cheaper for businesses to turn into usable sources of insight. Continue Reading