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introduction_aikaike

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  1. 1. Data Science Intro Regress [v. ri-gress] 1. to move backward Albert Anthony D. Gavino, Data Scientist
  2. 2. Topics CRISP DM model Phases of CRISP-DM History of Data Mining
  3. 3. CRISP-DM 1.0
  4. 4. Phases of CRISP-DM 1.0
  5. 5. Reverend Thomas Bayes (1763) Reverend Thomas Bayes was an English statistician, philosopher and Presbyterian minister who is known for having formulated a specific case of the theorem that bears his name: Bayes' theorem. 1763: paper was published Application Real Case: Uber Priors used by Uber: Rider Prior: this prior is about the user Popular place prior: restaurants, night life,museums Uber Prior: all uber riders go to certain places
  6. 6. Legendre & Gauss (1805) 1805 Adrien-Marie Legendre and Carl Friedrich Gauss applied regression to determine the orbits of bodies about the Sun. Hence the method of least squares (for computing the unknown parameters in the general regression model)
  7. 7. Alan Turing (1936) An "effectively computable" procedure is supposed to be one that can be performed by systematic application of clearly specified rules, without requiring any inspirational leaps or spontaneous intellectual insights
  8. 8. Hirotugu Aikaike & the AIC (1974) November 5, 1927 – August 4, 2009) Hirotugu was a Japanese statistician. In the early 1970s he formulated a criterion for model selection—the Akaike information criterion, which he thought of while riding the train. “On the morning of March 16, 1971, while taking a seat in a commuter train, I suddenly realized that the parameters of the factor analysis model were estimated by maximizing the likelihood and that the mean value of the logarithmus of the likelihood was connected with the Kullback- Leibler information number. This was the quantity that was to replace the mean squared error of prediction”
  9. 9. Data Science History 1943 McCulloch and Pitts wrote , they describe the idea of a neuron in a network. Each of these neurons can do 3 things: receive inputs, process inputs and generate output. 1989 The term “Knowledge Discovery in Databases” (KDD) is coined by . It was also at this time that he co-founded the also named . 1990s The term “data mining” appeared in the database community. Retail companies and the financial community are using data mining to analyze data and recognize trends to increase their customer base. 1992 Boser, Guyon and Vapnik suggested an improvement on the original support vector machine which allows for the creation of nonlinear classifiers. are a supervised learning approach that analyzes data and recognizes patterns used for classification and regression analysis. 2001 Although the term has existed since 1960s, it wasn’t until 2001 that William S. Cleveland it as an independent discipline. As per , DJ Patil and Jeff Hammerbacher then used the term to describe their roles at LinkedIn and Facebook.
  10. 10. Anthony Goldbloom, Kaggle (2010) Goldbloom (1983) born in Australia, founded Kaggle in 2010 as a Silicon Valley Startup that focused on predictive analytics.
  11. 11. Andrew Ng of Baidu, Coursera (2011) Andrew Yan-Tak Ng (born 1976) is Chief Scientist at Baidu Research in Silicon Valley. In addition, he is an associate professor in the Department of Computer Science at Stanford University. He is chairman of the board of Coursera, an online education platform that provides data science courses online. In 2011, Ng founded the Google Brain which developed very large scale artificial neural networks using Google's distributed computer infrastructure. Among its notable results was a neural network trained using deep learning algorithms that learned to recognize cats after watching only YouTube videos.
  12. 12. Branches of Data Science Natural Language Processing (NLP) Deep Learning Predictive Analytics Text Analytics Social Media Analytics Image Processing

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