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Big-data

Big data is a term for data sets that are so large or complex that traditional data processing applications are inadequate. Challenges include analysis, capture, data curation, search, sharing, storage, transfer, visualization, querying, updating & information privacy.
Big Data Bootcamp, Atlanta, Nov 3-5
This is a fast paced, vendor agnostic, technical overview of the Big Data landscape, targeted towards people who want to understand the emerging world of Big Data. Use code KDNUGGETS to save.
Accelerating Your Algorithms in Production with Python and Intel MKL, Sep 21
We will provide tips for data scientists to speed up Python algorithms, including a discussion on algorithm choice, and how effective package tool can make large differences in performance.
Python Overtaking R?
Did Python overtake R? We examine and compare 3 different blogs that deal with this question.
Top /r/MachineLearning Posts, August: Andrew Ng is back at it; Reinforcement Learning makes a splash; Fixing your ANN
Andrew Ng announces new Deep Learning specialization on Coursera; DeepMind and Blizzard open StarCraft II as an AI research environment; OpenAI bot beat best Dota 2 players in 1v1 at The Internatio...
Asimov’s 4th Law of Robotics
It seems Isaac Asimov didn’t envision needing a law to govern robots in these sorts of life-and-death situations where it isn’t the life of the robot versus the life of a human in debate, but it’s ...
Strata Data Conference – 3 reasons to attend, Sep 25-28, NYC
Data is driving business transformation. Come to Strata Data Conference and learn how to turn algorithms into business advantage, build modern data strategies, and spend quality time with experts. ...
Tackling Unstructured Data With Text Exploration – On-demand webcast
Discover how to use a platform to organize unstructured data to see the linkages between word usage and document of origin, see the themes in a word cloud, and use topic extraction and document clu...
I built a chatbot in 2 hours and this is what I learned
I set out to test two things: 1) building a bot is useless from a business perspective and 2) building bots is crazy tough. Here is what I learned.
Decoding AI: Making the Case for Artificial Intelligence
The question is no longer ‘can we get machines to do this or that’ (the answer is yes for most things you can think of), question now is ‘where all do we want to do it?’
Big Data or Big BS?
Data and analysis of data have, in some form, been used to aid decision making since ancient times. So why, after all these centuries are data and analytics not more embedded in corporate decision ...
Top KDnuggets tweets, Aug 30 – Sep 5: Python overtakes R, becomes the leader in #DataScience; Humble Book Bundle: #DataScience
Also: Pandas tips and tricks #Python #DataScience; How I replicated an $86 million project in 57 lines of code; Future #MachineLearning Class.
ACM Data Science Camp 2017, Oct 14, Silicon Valley
Data Science Camp is SF Bay ACM annual event combining sessions, keynote, and optional tutorial - an excellent opportunity to learn and connect with others, at very low cost.