Search results for private cloud

    Found 216 documents, 14209 searched:

  • 5 overriding factors for the successful implementation of AI

    Today AI is everywhere, from virtual assistants scheduling meetings, to facial recognition software and increasingly autonomous cars. We review 5 main factors for the successful AI implementation.

  • Find Out What Celebrities Tweet About the Most

    Word cloud is a popular data visualisation method. Here we show how to use R to create twitter word cloud of celebrities and politicians.

  • Accenture: Data Science Consultant

    Seeking a Data Science Consultant to strategically handle the massive amounts of information our clients collect today so that it may become their most valuable new asset, and to gain actionable insights from that data is critical to produce tangible results.

  • Accenture: Artificial Intelligence Analytics Sr Manager

    Seeking an Artificial Intelligence Analytics Senior Manager to build and drive Artificial Intelligence opportunities in the UK and Ireland. This person will be responsible for helping shape Accenture’s point of view on Artificial Intelligence.

  • Accenture: Big Data Engineer

    Seeking a Big Data Engineer for designing and implementing modern, scalable data pipelines for our clients, providing advisory services and thought leadership on the selection and deployment of commercial and open source tools, and more.

  • How will Big Data companies monetize data in 2018?

    In today’s data driven economy, Data is a strategic asset to a company and data monetization is prime focus of many companies. Let’s see how data monetization will be achieved in 2018.

  • When Data Science Is Not Enough: Deriving Signal from Maritime Observations

    We examine the limits of "data science-first" thinking - letting technical skills drive the analysis, and only later adding domain understanding.

  • The Internet of Things: An Introductory Tutorial Series

    In this series of post, the author will be presenting a set of Internet of Things technologies and applications in the form of tutorial in chapter form. Basic concepts are covered with an approachable style, not heaped in technical terms.

  • AI and Deep Learning, Explained Simply">Silver Blog, July 2017AI and Deep Learning, Explained Simply

    AI can now see, hear, and even bluff better than most people. We look into what is new and real about AI and Deep Learning, and what is hype or misinformation.

  • How GDPR Affects Data Science">Silver Blog, July 2017How GDPR Affects Data Science

    Coming European GDPR directive affects data science practice mainly in 3 areas: limits on data processing and consumer profiling, a “right to an explanation” for automated decision-making, and accountability for bias and discrimination in automated decisions.

  • How Feature Engineering Can Help You Do Well in a Kaggle Competition – Part 3

    In this last post of the series, I describe how I used more powerful machine learning algorithms for the click prediction problem as well as the ensembling techniques that took me up to the 19th position on the leaderboard (top 2%)

  • Unsupervised Investments (II): A Guide to AI Accelerators and Incubators

    A meticulously compiled list as extensive as possible of every accelerator, incubator or program the author has read or bumped into over the past months. It looks like there are at least 29 of them. An interesting read for a wide variety of potentially interested parties - far beyond only the investor.

  • Learn from Legends in Machine Learning, Open Source in 3 Days

    More than 400 of the sharpest minds in the industry will meet at Postgres Vision June 26-28 in Boston. The goal is to envision the future for enterprises striving to harvest greater strategic value and actionable insight from their data.

  • Data Science & Machine Learning Platforms for the Enterprise

    A resilient Data Science Platform is a necessity to every centralized data science team within a large corporation. It helps them centralize, reuse, and productionize their models at peta scale.

  • Open Source is Central to the Data Management Conversation, Boston, June 26-28

    Open source dominates the data management conversation. Postgres Vision, June 26-28, Boston, explores the business value realized from innovative solutions and strategies. Use code KDPV17 to save.

  • Unsupervised Investments: A Comprehensive Guide to AI Investors

    This article presents a list of 80 funds investing in Artificial Intelligence and Machine Learning.

  • “Data For Climate Action” Challenge – call for research proposals

    The challenge is to harness data science and big data from the private sector to fight climate change. Data scientists, researchers, and innovators - submit proposals at by 10 April 2017.

  • Gartner 2017 Magic Quadrant for Data Science Platforms: gainers and losers">Silver BlogGartner 2017 Magic Quadrant for Data Science Platforms: gainers and losers

    We compare Gartner 2017 Magic Quadrant for Data Science Platforms vs its 2016 version and identify notable changes for leaders and challengers, including IBM, SAS, RapidMiner, KNIME, MathWorks, Microsoft, and Quest.

  • Why Go Long on Artificial Intelligence?

    We are now at the right place and time for AI to be the set of technology advancements that can help us solve challenges where answers reside in data. While we have already seen a few AI bull and bear markets since the 50’s, this time it’s different. If I and others are right, the implications are immensely valuable for all.

  • First Deep Learning for coders MOOC launched by Jeremy Howard

    Leading Data Scientist and entrepreneur Jeremy Howard launches a free Deep Learning course that shows end-to-end how to get state of the art results, including a top place in a Kaggle competition.

  • How to Rank 10% in Your First Kaggle Competition

    This post presents a pathway to achieving success in Kaggle competitions as a beginner. The path generalizes beyond competitions, however. Read on for insight into succeeding while approaching any data science project.

  • Intellectual Ventures Lab: Sr. Machine Learning Algorithm Development Software Engineer

    Seeking a Senior Machine-Learning Algorithm Development Software Engineer to provide technical leadership to fast-paced machine-learning development projects.

  • How to Get Stuff Done at a Data Startup

    This post is a followup to how to structure data science teams, with a focus on how we get stuff done. The same principles we follow can be applied at your data startup or data science team.

  • FlyElephant 2.0, Big Data High-Performance Computing Platform

    FlyElephant is a platform for data scientists, engineers and scientists, which provides a ready-computing infrastructure for high-performance computing and rendering.

  • Internet of Things Key Terms, Explained

    This post will define 12 Key Terms for the Internet of Things, in straightforward manner.

  • 35 Open Source tools for Internet of Things

    If you have heard about the Internet of Things many times by now, its time to join the conversation. Explore the many open source tools & projects related to Internet of Things.

  • Interesting Things I Learned at SciPy 2016

    Learn about some interesting projects featured at SciPy 2016, brought to you by an attendee who put in the work to bring you this great list of projects.

  • Getting Started with Analytics: What’s the Upfront Investment?

    Everyone wants to leverage analytics, but should everyone dive into the deep end right away? Heed some sensible advice on getting started with analytics, and assessing the true upfront investment.

  • Gregory Piatetsky-Shapiro

    Gregory Piatetsky-Shapiro, Ph.D. is the Founder of KDnuggets, a leading site for Analytics, Big Data, Data Science, Data Mining, and Machine Learning. Gregory was a Read more »

  • 5 Best Practices for Big Data Security

    Lack of data security can not only result in financial losses, but may also damage the reputation of organizations. Take a look at some of the most important data security best practices that can reduce the risks associated with analyzing a massive amount of data.

  • Data Scientists – future-proof yourselves

    Here are 7 suggestions for Data Scientist to make themselves future-proof and get skills for a successful Data Science career in the future.

  • Microsoft is Becoming M(ai)crosoft

    This post is an overview and discussion of Microsoft's increasing investment in, and approach to, artificial intelligence, and how their philosophy differs from their competitors.

  • Turn your company into a data science-driven business in 6 steps

    Transforming your business with (big) data analytics and data-driven insights is not a one-time event, but a journey. Here are 6 steps to help enterprises become data-science driven business and enjoy benefits along the way.

  • What Developers Actually Need to Know About Machine Learning

    Some guidance on what, exactly, it is that developers need to know to get up to speed with machine learning.

  • Wind and Weather – Open Text Data Digest

    It’s soothing to watch the wind flows cycle and clouds form and dissipate. Now an app called Windyty lets you navigate real-time and predictive views of the weather yourself, controlling the area, altitude, and variables such as temperature, air pressure, humidity, clouds, or precipitation.

  • Simplilearn disrupts Big Data Industry with Masters and Flexi Pass Programs

    Simplilearn, the largest online certification training company, offers 3 separate Big Data Masters Programs, courses on Hadoop and Spark, its unique CloudLab, and certification.

  • Booz Allen Hamilton: Data Scientist

    Apply expertise in advanced analytics working with industry leading Cloud computing technologists and data scientists to solve large-scale, complex, and challenging business problems across the public and private sectors.

  • Avoiding Tunnel Vision in Peer Comparisons

    Comparing yourself to peers (benchmarking) lets you understand how you’re doing and identify performance gaps. Benchmarking is widespread but frequently misses useful and actionable insights. The proposed approach helps avoid the tunnel vision in benchmarking.

  • Are you trying to acquire Machine Learning Skills?

    Embarking on a journey through the lands of machine learning? Here are few important lessons like Feature Engineering, Model tuning, Overfitting, Ensembling etc. which you should keep in mind along the way.

  • Top Datapreneurs in data science

    A datapreneur is an entrepreneur focused on data science. Here is a great list of datapreneurs who created Data Products, Data Science Services, Data Science Training/Education, and Data Science Communities.

  • HP Big Data Helps Ford to Better Manage Fleets and Personalize Employee Drives

    HP-Ford partnership is leveraging Big Data for the next level of Telematics insights based intelligence.

  • Merkle: Data Operations Lead

    The ideal candidate has some Ad Ops experience and is familiar with the ad:tech ecosystem, including DMP, DSP, Facebook, ad servers, mobile platforms, portals, and exchanges as well as traditional offline processes.

  • Best Big Data, Data Science, Data Mining, and Machine Learning podcasts

    We present the top 12 Data Science & Machine Learning related Podcasts by popularity on iTunes. Check out latest episodes to stay up-to-date & become a part of the data conversations!

  • Exclusive Interview: Matei Zaharia, creator of Apache Spark, on Spark, Hadoop, Flink, and Big Data in 2020

    Apache Spark is one the hottest Big Data technologies in 2015. KDnuggets talks to Matei Zaharia, creator of Apache Spark, about key things to know about it, why it is not a replacement for Hadoop, how it is better than Flink, and vision for Big Data in 2020.

  • Machine Learning Wars: Amazon vs Google vs BigML vs PredicSis

    Comparing 4 Machine Learning APIs: Amazon Machine Learning, BigML, Google Prediction API and PredicSis on a real data from Kaggle, we find the most accurate, the fastest, the best tradeoff, and a surprise last place.

  • April 2015 Analytics, Big Data, Data Mining Acquisitions and Startups Activity

    Apr 2015 acquisitions, startups, and company activity in Analytics, Big Data, Data Mining, and Data Science: Microsoft + RevolutionR, Most-Funded Startups, VC says boom not bubble - look at valuations, and more.

  • Growth Intelligence: Developer, Big Data

    Help collect and process data on millions of companies from many sources, scale back-end data platform, build and improve web application, analyse data, and extract useful insights. Our clients include Google, American Express and Vodafone.

  • Growth Intelligence (London): Senior Data Scientist

    Help us take the messy data we have on millions of companies and push it through a data pipeline into a web based search and recommendation engine. Our clients include Google, American Express and Vodafone.

  • Interview: Emmanuel Letouzé, Data-Pop Alliance on the Role of Big Data in Economic Development

    We discuss the emerging Big Data ecosystem, its key players, and the severe consequences of inadequate statistical capabilities across many African nations.

  • Algorithmia Tested: Human vs Automated Tag Generation

    Algorithmia, the marketplace for algorithms, can be a platform for hosting APIs to do a plethora of text analytics and information retrieval tasks. Automatic post tagging is done in this case study to demonstrate the effectiveness and ease-of-use of the platform.

  • Additions to KDnuggets Directory in February

    Big Data Paris, Wharton Conf: Successful Applications of Customer Analytics, analytics consulting firms, Georgetown MS in Analytics, MSc in Data Science in France, and more meetings, companies, education, and solutions.

  • Analytics Outsourcing to India: Should or Shouldn’t?

    Outsourcing analytics talent to India will continue to grow as a trend as evidenced by the increasing number of Fortune 500 companies participating in the practice.

  • Big Data Could Revolutionize Healthcare. Will We Let it?

    The power to access and analyze enormous data sets can improve our ability to anticipate and treat illnesses. The benefits for society are just too great, and they won’t be ignored for long.

  • Interview: John Schitka, SAP on The Type of Data Scientists We Need

    We discuss the focus areas of Big Data strategy at SAP, how SAP is leading the competition, the kind of data scientists we need, advice and more.

  • Interview: John Schitka, SAP on How to Get Started with Big Data

    We discuss the current perceptions of Big Data, challenges for Big Data consumerization, dealing with the talent gap, and business strategy for Big Data.

  • KDnuggets™ News 15:n01, Jan 7: Clever methods of overfitting; 5 Analytics Rules to cut thru the Hype

    11 Clever Methods of Overfitting and how to avoid them, Data Mining and Text Analytics of World Cup 2014, iMath Cloud Data Science Platform beta, Platfora CEO on Insightful Analytics for Big Data, and more analytics, big data, data science, and data mining stories.

  • BIME Business Intelligence Predictions for 2015

    Business intelligence in 2015 will see greater social media involvement, data mining applications, health data analysis, data-driven drones, and BI in the cloud.

  • Top 10 Big Data Companies by Revenue

    IBM, HP, Dell, and SAP lead the list of Big Data companies with the most revenue from big data hardware, software, and IT services.

  • October 2014 Analytics, Big Data, Data Mining Acquisitions and Startups Activity

    October 2014 acquisitions, startups, and company activity in Analytics, Big Data, Data Mining, and Data Science: DrivenData, Map-D, Microsoft buys Equivio, Alteryx, Cazena, Ello, Zoomdata, Cloudera buys DataPad, Tibco goes private.

  • KDnuggets™ News 14:n30, Nov 19

    Features | Software | Opinions | Interviews | Reports | News | Webcasts | Courses | Meetings | Jobs | Academic | Publications | Tweets Read more »

  • Wikibon Big Data Capital Markets Day – Big Data NYC 2014

    One of the biggest events at Big Data NYC 2014 was the insightful presentation by Jeff Kelly from WikiBon. We provide here the key takeaways.

  • KDnuggets™ News 14:n26, Oct 8

    Features | Software | Opinions | Interviews | News | Webcasts | Courses | Meetings | Jobs | Academic | Publications | Tweets | CFP Read more »

  • Upcoming Webcasts on Analytics, Big Data, Data Science – Sep 30 and beyond

    Not all graph databases are created equal, Evolution of Classification, Governing Big Data, Big Data Visualization, Best Practices for Applying Advanced Analytics in Hadoop, and more.

  • Upcoming Webcasts on Analytics, Big Data, Data Science – Sep 2 and beyond

    Streaming Analytics, Analytical Lifecycle, Modern Regression Analysis, Hadoop for Machine Learning, NASA Earth Science Data, Strata + Hadoop NYC preview, Ontotext, and more.

  • Containers: The Enabler of YARN

    The evolution of a data-center operating system is discussed along with the underlying challenges and approaches being followed. Containers play a big role in enabling the required abstraction and deliver additional benefits.

  • Interview: Leo Meyerovich, Graphistry on Browser-based Interactive Big Data Visualization

    We discuss the merits of Superconductor architecture, comparison with current JavaScript visualization library, use cases, future plans, launch of Graphistry, visualization trends, and more.

  • Business Analytics Innovation Summit 2014 Chicago: Day 2 Highlights

    Highlights from the presentations by Business Analytics leaders from State of Illinois, Navistar, BMO Harris Bank and McGraw Hill Education on day 2 of Business Analytics Innovation Summit 2014 in Chicago.

  • Top KDnuggets tweets, Jun 16-17: You cannot afford to ignore next #AI wave; 5 Companies doing #BigData Right

    You cannot afford to ignore next #AI wave - see early leaders; 5 Companies doing #BigData Right: Amazon, British Airways, eBay, Otto group, Netflix; Data Mining 200 years of Patents shows that invention is combinatorial; Cartoon: Big Data and World Cup Football.

  • Lynn Goldstein, Chief Data Officer, NYU on the Need for Data Governance

    We discuss the role of Data Governance, establishing Big Data accountability, impact of Data Governance on Data Quality, and assessing the education available for Data Governance.

  • Stacking the Deck: The Next Wave of Opportunity in Big Data

    A leading venture capitalist explains why Big Data infrastructure market is mostly mature and where lies the next big area of opportunities related to Big Data.

  • FirstFuel: Data Scientist

    FirstFuel Software is using energy analytics to help utilities and government agencies deliver scalable energy efficiency. Data Scientist will develop state of the art Statistical/Machine Learning algorithms and deploy them to a scalable, secure, cloud-based architecture.

  • Exclusive Interview: Peter Bruce, President

    We discuss the mission of, selection of analytics courses and certificates, the future of analytics education, MOOCs, are Statistics disconnected from Big Data, the role of a data scientist, and more.

  • January Analytics, Big Data, Data Mining Companies and Startups Activity

    January 2014 acquisitions, startups, and company activity in Analytics, Big Data, Data Mining, and Data Science: DeepMind, Avigilon, TaKaDu, Nest, Path, FirstFuel, API Healthcare, Kana Software, ImgUR, IMS Health.

  • Bioinformatics Companies

    A B C D E F G H IJ K L M N O P Q R S T U V W XYZ A2IDEA is Read more »

  • September Analytics, Big Data, Data Mining companies and startups activity

    The September 2013 acquisitions, startups, and company activity in Analytics, Big Data, Data Mining, and Data Science: SAP buys KXEN, Rocket Fuel IPO, Clarabridge Indisys, Narrative Science, Practice Fusion and more.

  • The Big Data Landscape, 2013 Edition

    The The Big Data Landscape includes over 100 companies and Big Data vendors of all sizes, public and private market investors, and technology buyers.

  • Data Mining / Analytic News Briefs, Jun 2013

    Features (13) | Software (5) | Courses, Events (14) | Jobs | Academic | Competitions (4) | Publications (23) | News Briefs (15) Hunk: Splunk Analytics Read more »

  • Kaggle Connect Data Science Consulting

    Kaggle Connect is a consulting platform that connects companies to the top Kaggle competitors.

  • 11 segments of Big Data Ecosystem, according to Sqrrl

    Sqrrl, a Big Data startup founded by the ex-NSA engineers, breaks down Big Data Market into 11 segments.

  • Strata Conference Reports and Highlights

    Highlights from Strata Feb 2013 Conference on Big Data, covering Hadoop, Python Data Science, game data mining, Groundhog day, data thoughtcrime, situational awareness, and more.

  • October Analytics, Big Data, Data Mining companies and startups activity

    The October 2013 acquisitions, startups, and company activity in Analytics, Big Data, Data Mining, and Data Science: Monsanto buys Climate Corp for $1.1B, MongoDB raises $150M, Facebook buys Onavo, Pivotal buys Xtreme Labs.

  • 2013 Acquisitions in Analytics and Big Data

    We review 2013 acquisitions in Analytics and Big Data, by Actian, EMC, Facebook, Google, IBM, Twitter, WalmartLabs and more. What is the worth of an engineer in acqui-hire?

  • Consulting Companies in AI, Analytics, Data Science, and Machine Learning

    A B C D E F G H I J K L M N O P Q R S T U V W XYZ 4i, Read more »

  • KDnuggets™ News 13:n12, May 8

    Features (9) | Software (4) | Webcasts (3) | Courses, Events (1) | Meetings (3) | Jobs (9) | Academic (3) | Competitions (1) | Publications Read more »

  • McDowell Interview: PASS Business Analytics Conference, Microsoft Data Mining

    I interviewed Douglas McDowell about the PASS Business Analytics Conference, SQL Server, Microsoft Data Mining, less known but useful features of SQL, NodeXL, Big Data and more.

  • KDnuggets™ News 13:n03, Feb 13

    Features (9) | Software (6) | Webcasts (2) | Courses, Events (3) | Jobs (6) | Meetings (5) | Academic (1) | Competitions (4) | Publications Read more »

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