Andmekaeve 2013/14 kevad

Links

Data Science skills and how to learn them:

http://dataconomy.com/top-10-data-science-skills-and-how-to-learn-them

• Links to the practice session 1:
  • Quora discussion about example problems in Data mining (suggested by Anya). There are even some hints given on where to get data from and how to start analyzing it.
  • xkcd - machine learning and data mining humor in the form of comics.
  • WolframAlphaOnline - find this useful online tool for answering math and probability questions. It also knows the answer to the meaning of life question.
  • Milk video - youtube video about milk from the practice sessions.
  • Stackexchange - discussion on the difference between Data mining, Machine Learning, AI and statistics (I promised it to some of you).
• Links to the practice session 2:
  • Titanic Data
  • Solution to the exercise 6 (has to be tuned anyway)
• Links to the practice session 3:
  • Interestingness Measures for Association Patterns : A Perspective
  • Some insights about the measures of interestingness
• Links to the practice session 4:
• Links to the practice session 5:
  • Visualizing Dendrograms in R
  • Machine Learning
• Links to the practice session 6:
• Links to the practice session 7:
  • k-Means Clustering Example
  • Clustering playing cards with K-means
  • How to estimate sufficient number of clusters for your data
  • How self organizing maps algorithm works
  • Animated SOM
  • Self-organizing maps visualization
• Links for the practice session 8:
  • none can recollect now
• Links for the practice session 9:
  • article written by Konstantin Tretyakov about Machine Learning Techniques in Spam Filtering.
  • presentation about Bayes Classifier and Naïve Bayes, might be useful for those who still have questions.
  • Summer School AACIMP on Data analysis, the early deadline is May 1, so decide quicker.
• Links for the practice session 10:
• Links for the practice session 11:
  • How SVM algorithm works
  • Learning rule of the perceptron algorithm visualized on a small example dataset
  • Fantastic kernelized SVM clusters points that form a circle in 2-D space
• http://www.kdnuggets.com/2014/03/machine-learning-7-pictures.html

R tutorial:

Source code file from R workshop. Video from workshop can be found here.

MOOC-s

• Google - making sense of data - https://datasense.withgoogle.com/preview
• In-depth introduction to machine learning in 15 hours of expert videos

Some media coverage:

• http://www.wired.com/wiredscience/2014/01/how-to-hack-okcupid/all/
• http://www.theatlanticcities.com/jobs-and-economy/2013/06/map-iphone-users-any-city-and-you-know-where-rich-live/5961/
• Google Announces An Online Data Interpretation Class For The General Public
• Big Data vendors

Tools, software, visualisation, etc...

• https://plot.ly/ Plotly (incl. APIs for Python, R, MATLAB, Julia, Perl, REST, Arduino, Raspberry Pi)