Data Science



Location Powers: Super Hero of Location

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The explosive availability of data about nearly every aspect of human activity along with revolutionary advances in computing technologies is transforming geospatial data science. The shift from data-scarce to data-rich environment comes from mobile devices, remote sensing and the Internet of Things. Nearly all of this data has components of location and time. Innovations in cloud computing and big data provides methods to perform data analytics at exceedingly large scale and speed. The development of intelligent systems using knowledge models and their impact on our insights and understanding will be focus of the Location Powers: Data Science Summit.


Nordic Data Science and Machine Learning Summit 2019 – Accelerating Data & AI Innovation

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Nordic Data Science and Machine Learning Summit is an annual event bringing together the Data Science Community in the Nordics to share ideas, and discuss ways to harness the full potential of Data Science and Machine Learning. The agenda is suited to guide you through the process of extracting knowledge from data by using the latest methodologies, tools and algorithms. With domestic and international speakers on stage, workshops, interactive panel discussion and plenty of learning and networking activities in the exhibition area, the Nordic Data Science and Machine Learning Summit is the place to be for all professionals and organisations working with utilization of Data Science, Machine and Deep Learning, to innovate and improve their business. For those who would like to get an opportunity to dive deep into a particular topic, process, or technology, we are setting up some Hands-on three-hour workshops with coffee break in-between. Three of the workshops with be technical and one on strategy and value.


Data Futurology - Data Science, ML and AI From Top Industry Leaders • A podcast on Anchor

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Quotes: "The best way to develop knowledge in any area is to experience it." "It is easier to sit in an office and assume the world works in a certain way." "Don't be in startups because it's cool, try and find a path that meets your own needs." "Working with startups is a lot of broader outreach and helping the community understand what is possible." Thank you to our sponsors: Fyrebox - Make Your Own Quiz! RMIT Online Master of Data Science Strategy and Leadership Gain the advanced strategic, leadership and data science capabilities required to influence executive leadership teams and deliver organisation-wide solutions. Visit online.rmit.edu.au for more information And as always, we appreciate your Reviews, Follows, Likes, Shares and Ratings. Thank you so much for listening.


Academics adopt AI-powered application and data integration

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Today's announcement was made from the EDUCAUSE Annual Conference taking place this week in Chicago, IL. To learn more about SnapLogic for higher education, stop by SnapLogic Booth #1114 on the conference showfloor. Today's progressive universities and colleges are embracing the cloud, unifying their applications and systems, and putting data at the center of their strategies to enrich the experience of their diverse constituents: Student Engagement: The majority of incoming students are digital natives who expect consistent, real-time access to information on housing, parking, class schedule, grades, financial aid, and more, ideally delivered via a one-stop-shop online portal. Data-driven Faculty: Faculty are leveraging digital tools to tailor, personalize, and optimize learning for students, both in the classroom and via online courses. At the individual student level, many professors are leveraging data to identify students who may be struggling and require additional attention.


Formatting NFL data for doing data science with Python

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No matter what medium of content you consume these days (podcasts, articles, tweets, etc.), you'll probably come across some reference to data. Whether it's to back up a talking point or put a meta-view on how data is everywhere, data and its analysis are in high demand. As a programmer, I've found data science to be more comparable to wizardry than an exact science. I've coveted the ability to get ahold of raw data and glean something useful and concrete from it. This got me thinking about the difference between data scientists and programmers.


The new way your boss can tell if you're about to quit your job Produced by Advertising Publications

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IBM wants to keep its employees from quitting. And it's using artificial intelligence to do it. In a recent CNBC interview, CEO Ginni Rometty said that thanks to AI, the tech and consulting giant can now predict with 95% accuracy which employees are likely to leave in the next six months. The "proactive retention" tool -- which IBM uses internally but is also selling to clients -- analyzes thousands of pieces of data and then nudges managers toward which employees may be on their way out, telling them to "do something now so it never enters their mind," Rometty said. IBM's efforts to use AI to learn which employees might quit is one of the more high-profile recent examples of the way data science, "deep learning" and "predictive analytics" are increasingly infiltrating the traditionally low-tech human-resources department, arming personnel chiefs with more rigorous tools and hard data around the tricky art of managing people.


Legal Analytics Dictionary: Eight Terms You Should Know

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If you remember the days of cassette tapes, floppy disks and flip phones, then we don't need to tell you how quickly technology is moving lately. Now it seems we're running headlong into the era of artificial intelligence. Yes, smart computers capable of learning and adapting to solve complex problems. We're not quite to HAL yet, but it seems technology is getting there. And with these new technologies comes a new vocabulary.


SOCAL 2019 – IDEAS

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Our multiple tracks offer a diverse selection of trending topics, including Artificial Intelligence & Automation, Big Data and Infrastructure, Machine Learning and Deep Learning, Data Visualizations, Data Analytics, Healthcare & IOT, Business Practice, and Data Security. The topics covered will involve many industries, including Healthcare, FinTech, Retail, Media, Manufacturing, Insurance, Education, E-Commerce, and more. Both industry-leading companies and startup firms will present at the conference and demonstrate innovative data analytics technologies. Previous featured speakers included those from IBM, Intel, Capital One, City of Los Angeles, Caltech, Alibaba, Accenture AI, and several other industry-leading companies.


The insideBIGDATA IMPACT 50 List for Q4 2019 - insideBIGDATA

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The team here at insideBIGDATA is deeply entrenched in following the big data ecosystem of companies from around the globe. Our in-box is filled each day with new announcements, commentaries, and insights about what's driving the success of our industry so we're in a unique position to publish our quarterly IMPACT 50 List of the most important movers and shakers in our industry. These companies have proven their relevance by the way they're impacting the enterprise through leading edge products and services. We're happy to publish this evolving list of the industry's most impactful companies! The selected companies come from our massive data set of vendors and industry metrics.