Link roundup, week 32/2012

Sunday, August 12. 2012

Link roundup, week 32/2012

A Strategic Mistake With Big Data — International Institute for Analytics

tags: bigdata opinion
- Bill Franks
- That mistake is the development of a siloed, distinct big data strategy
- strategy for big data is a new facet of their overall enterprise data and analytic strategy
- the mess that many multi-channel retailers got themselves into through their entry into e-commerce
- retailers launched distinct e-commerce divisions. Some were even separate legal entities. As opposed to viewing e-commerce as a new facet of an overall retail strategy
- distinct processes and distinct infrastructure was created
- provide a consistent experience for customers across channels
- go into a store and grab a product and then find that same product on the retailer’s website. Guess what? They have no way to match those products
- separate, non-integrated strategies for big data will likely end up with systems and processes that are very difficult to integrate
- integrate big data into the overall infrastructure and current and future analytic processes
Machine learning system can ID cities via pics | Cutting Edge - CNET News

tags: machinelearning computervision datamining research technology
- The system automatically picks out relevant architectural details from photos
- the details woven into the urban fabric that form a pattern
- computers are learning to ID your city just by looking at random photos
- Google Street View images of Paris, London, New York, and Barcelona
- features like the street signs, balconies, and lampposts of Paris to be distinct
- lack of stylistic coherence in American cities
- presented at Siggraph 2012
- emerging field of visual data mining, which is more complex than looking for patterns in text or numbers
- Alexei Efros
- we wish to automatically build a digital visual atlas of not only architectural but also natural geo-informative features for the entire planet
Interviewing data scientist candidates? Ask these questions

tags: datascience career opinion
- “It’s way over-hyped,” said Franks
- chief analytics officer for the data warehouse appliance vendor Teradata
- “softer skills.”
- “data artist.”
- data scientists are those that are able to understand the business problem; they’re able to apply creativity and present the results well
- intuition, which is hard to teach
- five core areas I look at
- Commitment
  - 1.
- Creativity
  - 2.
- thought process they went through deciding what to do. Someone who’s not creative is going to give me a list of the steps they went through one-by-one more from a technical perspective
- Business savvy
  - 3.
- what I want to hear is not just some technical reasons
- Knowing how much information to give to the non-technical people
- Presentation
  - 4.
- specific presentation as part of the interview process
- intuition
  - 5.
- art or music or some other type of creative area

Hype Cycle for Cloud Computing 2012 (JPEG, 1221×839)

tags: bigdata technology graphics
Hype Cycle for Cloud Computing Shows Enterprises Finding Value in Big Data, Virtualization - Forbes

tags: bigdata technology graphics
- 8/04/2012
- Big Data will deliver transformational benefits to enterprises within 2 to 5 years
- by 2015 will enable enterprises adopting this technology to outperform competitors by 20%
- By 2014 the Personal Cloud will have replaced the personal computer
Peta-governance? Controlling the explosion of Big Data models will prove difficult | LinkedIn

tags: datascience bigdata opinion
- you will soon be swamped with models
- many in-production churn models
- does it fit the latest customer data
- compared with various challenger models?
- responsibility for approval of the latest and greatest model
- more and more models
- developed in more and more tools and languages
- with more and more variables
- from more and more sources
- in more and more business processes
- demands tools such as IBM SPSS Collaboration and Deployment Services
- life-cycle management of models
- check in/check-out, change tracking, version control, and collaborative development and validation
Machine Learning as a Service & Big Data Analytics | Licensing wise.io LLC

tags: machinelearning bigdata programming
- wiseRF, is a fast, memory efficient, and scalable implementation of Random Forest
- C++ API hooks and Python bindings
- soon entering a private beta of our hosted platform offering Machine Learning as a Service

And now a bunch of interesting upcoming online classes, ordered by start date:

Web Intelligence and Big Data | Coursera

Seems to be focused on the tech level

tags: bigdata education video lectures
- big-data platforms based on the ‘map-reduce’
- 27 August 2012 (10 weeks long)
- Search, Indexing
- Analyzing Sentiment
- Databases and their evolution
- Classification, Clustering, and Mining
- Dealing with Uncertainty
- Predictive Analytics
Neural Networks for Machine Learning | Coursera

Probably too specialized for my scope

tags: machinelearning education video lectures
- speech and object recognition, image segmentation, modeling language
- 17 September 2012 (8 weeks long)
- proficiency in Matlab, Octave or Python
- understand what a probability density is
Social Network Analysis | Coursera

SNA is *not* (necessarily) about social media. Probably too specialized as well, not sure if I should sign up.

tags: datamining education video lectures
- theory and computational tools
- September 2012 (8 weeks long)
- nodes, edges, adjacency matrix, one and two-mode networks, node degree
- Gephi
- Random network models
- breadth-first search
- average shortest path
- betweenness, closeness, eigenvector centrality (+ PageRank)
- clustering, community structure
- R statistical programming language along with NetLogo
- Gephi for visualization and analysis
- interactive demonstrations will be primarily in NetLogo
Mathematical Biostatistics Boot Camp | Coursera

The “bio-” will not really play a role

tags: statistics education video lectures
- fundamental probability and statistical concepts used in elementary data analysis
- small amount of linear algebra and programming are necessary
- 24 September 2012 (7 weeks long)
- probability distributions and their properties
- statistical likelihood
- confidence intervals
- R statistical programming language
Computing for Data Analysis | Coursera

tags: statistics r programming education video lectures
- learn to program in R
- modern statistical methods
- 24 September 2012 (4 weeks long)
- - Software for Data Analysis by John M. Chambers (Springer)
  - S Programming by Brian D. Ripley and William N. Venables (Springer)
  - Programming with Data by John M. Chambers (Springer)
- two large programming assignments
- How is this course different from “Data Analysis”?
  This course will focus on developing the programming skills
- will not focus on teaching properties of specific statistical algorithms
Data Analysis | Coursera

tags: datamining statistics education video lectures
- 22 January 2013 (8 weeks long)
- Big Data
- applied statistics course focusing on data analysis
- statistical methods like linear regression, principal components analysis, cross-validation, and p-values
- R statistical programming language
- How is this course different from “Computing for Data Analysis”?
  This course will focus on how to plan, carry out, and communicate analyses of real data sets
Scientific Computing | Coursera

tags: computerscience education video lectures
- To Be Announced
- MATLAB
- graphical techniques for information presentations
Introduction to Data Science | Coursera

tags: datascience education video lectures
- basics of data science
- practical experience programming massive databases
- To Be Announced
- MapReduce
- algorithms for data mining
- statistical modeling
- Bill Howe is the Director of Research for Scalable Data Analytics
- database design
- SQL, NoSQL, and NewSQL
- Algorithm design in Hadoop
- statistical analysis at scale
- data mining
- Case studies in analytics
- programming experience with Java or Python
- familiarity with databases
- Mining of Massive Datasets
- Professional NoSQL
- two exams
- quiz and a programming assignment
- Amazon Web Services or Microsoft Azure cloud services
SML: Scalable Machine Learning

Links to lengthy YouTube videos, recordings of slide-based classroom talks. Not sure if too useful.

tags: machinelearning education video lectures
- Instructor: Alex Smola
- 2 Statistics
- 5 GLM
- 6 Kernels
- 9 Graphical Models

Posted from Diigo. The rest of my favorite links are here.

Posted by Stephan Paukner in Data Science at 19:28 | Comments (0) | Trackbacks (0)

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