data mining


SnapLogic Introduces Self-Service Solution for End-to-End Machine Learning

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WIRE)--SnapLogic, provider of the #1 intelligent integration platform, today announced SnapLogic Data Science, a new self-service solution to accelerate the development and deployment of machine learning with minimal coding. Through SnapLogic's drag-and-drop interface, data engineers, data scientists, and IT/DevOps teams can use SnapLogic Data Science to manage and control the entire machine learning lifecycle – including data acquisition, data exploration and preparation, model training and validation, and model deployment – all from within the SnapLogic integration platform. SnapLogic Data Science breaks down traditional barriers that can undermine machine learning initiatives by providing a common platform for machine learning visibility and collaboration across teams including data engineering, data science, IT, DevOps, and development. According to our recent research with Vanson Bourne, 68% of IT decision-makers consider artificial intelligence and machine learning as vital to accelerating their transformation projects. At the same time, McKinsey Global Institute predicts that the U.S. alone will be short 250,000 data scientists by 2024.


SnapLogic Introduces Self-Service Solution for End-to-End Machine Learning

#artificialintelligence

WIRE)--Nov 14, 2018--SnapLogic, provider of the #1 intelligent integration platform, today announced SnapLogic Data Science, a new self-service solution to accelerate the development and deployment of machine learning with minimal coding. Through SnapLogic's drag-and-drop interface, data engineers, data scientists, and IT/DevOps teams can use SnapLogic Data Science to manage and control the entire machine learning lifecycle – including data acquisition, data exploration and preparation, model training and validation, and model deployment – all from within the SnapLogic integration platform. SnapLogic Data Science breaks down traditional barriers that can undermine machine learning initiatives by providing a common platform for machine learning visibility and collaboration across teams including data engineering, data science, IT, DevOps, and development. According to our recent research with Vanson Bourne, 68% of IT decision-makers consider artificial intelligence and machine learning as vital to accelerating their transformation projects. At the same time, McKinsey Global Institute predicts that the U.S. alone will be short 250,000 data scientists by 2024.


SnapLogic Data Science set to accelerate deployment of machine learning models

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SnapLogic recently joined Vanson Bourne for the'Busting Through Digital Transformation Roadblocks' research study, surveying 500 IT decision makers from medium to large firms in the US and UK to gain insight into the issues impeding digital transformation. The study found that 68% of those surveyed view AI and machine learning technology to be integral to digital transformation, but an industry-wide shortfall in ML expertise limiting the tech's uptake was found by a separate McKinsey Global Institute study. The SnapLogic Data Science self-service solution will enable companies to rapidly build and deploy machine learning programs without the need for advanced coding, circumventing the issue of limited expertise by increasing the accessibility and ease with which machine learning systems can be constructed and integrated into existing models. Through Data Science's drag-and-drop-based UI, engineers, data scientists, and DevOps teams will be able to coordinate data acquisition, data analysis and preparation, model training and validation, through to full deployment. "Every enterprise in every industry will need to employ AI and machine learning in order to keep pace with today's most progressive businesses," said Greg Benson, SnapLogic's Chief Scientist, in the firm's press release.


In 2018, Data Will Put the Human Back into Human Experience

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In this article, Part 1 of the latest in his series exclusive to Data Makes Possible, Dr. Kirk Borne, Principal Data Scientist for Booz Allen Hamilton, explains the importance and value proposition of improving the human experience in the digital enterprise, and why the year of experience must include customers, end-users, employees, and any other stakeholders. A few years ago, I heard someone describe their data product in this way: "analytics at the speed of your business." Well, no disrespect intended, but I think they got the message backwards. Because business is no longer able to keep up with the flood of data that is coming in, from forces and sources everywhere: social, mobile, internet, intranet, images, video, audio, and documents. Consequently, what you really need is business at the speed of your data!


Big Data and Artificial Intelligence - DZone Big Data

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Recently, I gave a two hour lecture on "Big Data and Artificial Intelligence," to use some buzzwords, as asked. More honestly, it will be on (new) data and (new) algorithms for predictive modeling.


Upstream O&G could save $75B annually using big data » Kallanish Energy News

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The upstream oil and gas industry could save up to $75 billion a year by 2023 with the deployment of so-called "big data," new research by consultancy Wood Mackenzie reveals. Embracing advances in analytics, machine learning and artificial intelligence could pay big dividends for the industry. These savings can be realized at every stage of the upstream lifecycle, Kallanish Energy learns. "Digitalization offers multiple prizes in exploration. The biggest would be to uncover new resources … but anyone with a competitive advantage in exploration would have a material advantage in licensing or M&A," Greig Aitken, principal analyst in Wood Mackenzie's corporate analysis team, said Monday.


Advanced AI and big data methods to tackle dementia

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Sports concussions, Parkinson's disease, and hormone therapy for cancer - all can have memory loss as symptoms. But do the biochemical processes of each type of memory loss have anything to reveal about the memory loss that is part of Alzheimer's disease? Rong Xu, PhD, recently received a total of $5 million for two projects that will use big data methods for a comprehensive look at a range of factors that may inform the mechanism of Alzheimer's and related dementia. "Vast amounts of data from seemingly unrelated sources present opportunities to researchers who aim to extract information that would help develop drugs or treatments," Says Xu, "This is especially true for diseases and conditions that may involve multiple genetic variations and that also have social or environmental influences." Xu is an associate professor at the Case Western Reserve University School of Medicine's Department of Population and Quantitative Health Sciences.


Data Digest: Trends, Charitable Applications, and AI Improvement for Big Data Transforming Data with Intelligence

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Read about new big data practices, how big data is being applied for good purposes, and how AI and NLP are changing the use of big data. As the use of big data continues to grow, many new practices are emerging for 2019. Read about five data science projects leveraging big data to tackle huge projects for social good. Applying AI and natural language processing is driving new value and innovation from big data.



Machine Learning Tutorial for Beginners - Learn Machine Learning - DataFlair

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In this machine learning tutorial, we are going to discuss the detailed what is Machine Learning and the difference between data mining and machine learning. Moreover, we will discuss different types of Machine Learning and different approaches to Machine Learning. Machine Learning is a science to make the machine capable of taking the decision itself. These systems also have the ability to learn from past experience or analyze historical data. It provides results according to its experience. So, let's start the Machine Learning Tutorial.