Predictive analytics and big data tutorial
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This presentation covers data science buzz words, big data introduction, predictive analytics, and model building methods. Structured vs unstructured. Supervised learning vs unsupervised learning.
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Predictive analytics and big data tutorial
- 1. Ben Taylor @bentaylordata Predictive Analytics / Data Science
- 2. Presentation Objectives • Enable you to be smarter than your prospect (data history / lingo) • Motivate you to be unstoppable and hyper-confident • Motivate you to begin looking for data driven opportunities • Motivate you to become a data scientist
- 3. "What the hell is cloud computing?" -Larry Ellison, CEO Oracle
- 4. What is cloud computing? ?
- 5. What is big data? Big data includes datasets or problems which exceed the capacity of a single computer and require a distributed data access system. The concept of "big" is relative to the conventional systems and technology and is subject to change in the future with advances in memory and storage solutions. http://www.pcmag.com/article2/0,2817,2453838,00.asp
- 7. What is a data scientist?
- 8. What is a data scientist? Engineering Finance Economics Mathematics Computer Science Physics Data Science 6-10yrs Python Bootcamp $8,000 (3 months) $16,000-$4,000 (3 months) $115K avg
- 9. What is a data scientist?
- 10. What is a data scientist? Master Builder
- 11. What is a data scientist? Reality distortion: Hyper-confidence
- 13. Data Scientist = Peacock
- 15. Smartest pirate 0 20 40 60 80 100 120 140 160 180 200 0 200 400 600 800 1000 1200 1400 Ships captured Treasurechests
- 16. Humans Algorithms VS 0 20 40 60 80 100 120 140 160 180 200 Ships captured NA
- 17. Humans Algorithms VS 0 20 40 60 80 100 120 140 160 180 200 Ships captured German (1795), French (1806) 0 20 40 60 80 100 120 140 160 180 2 0 200 400 600 800 1000 1200 1400 Ships captured Treasurechests
- 18. Humans Algorithms VS 1997, IBM deep blue Kasparov
- 19. Humans Algorithms VS 2011, IBM Watson Ken Jennings & Brad Rutter
- 20. Humans Algorithms VS 2014, HireVue Iris Hiring Panel
- 21. Prediction process Raw data Data munging Training Model
- 22. Data munging Prediction process Raw data Feature selection Training Model Data cleaning Clean data
- 24. Data munging Prediction process Raw data Feature selection Training Model Data cleaning LSR, SVM, RANDOM FOREST, NAÏVE BAYESIAN, NEURAL NET
- 25. Missing values + categorical @bentaylordata
- 27. Data munging Prediction process Raw data Feature selection Training Model Data cleaning LSR, SVM, RANDOM FOREST, NAÏVE BAYESIAN, NEURAL NET Retail > 15, Engineering > 95 > 5.67
- 28. Resume model
- 29. Resume model
- 30. Data munging Prediction process Raw data Feature selection Training Model Data cleaning LSR, SVM, RANDOM FOREST, NAÏVE BAYESIAN, NEURAL NET Retail > 15, Engineering > 95 GPA, Colleges, Hobbies > 5.67
- 31. Text deeper dive
- 34. Sentiment
- 35. Given data, find cat? dog? @bentaylordata
- 36. Talk like a data nerd @bentaylordata
- 39. Data Lingo Supervised vs unsupervised learning Supervised: Training set provided. Unsupervised: No training set, clustering based on similar attributes.
- 40. Data Lingo Analytic Layers Descriptive Analytics: Telling a data story, plotting, or visualization. Predictive Analytics: Predict future outcomes, usually trained on a historical training set Prescriptive Analytics: Using the insight from your predictive model to proactively change something Interview/Interaction Analytics: Any analytics surrounding the interview or interaction.
- 41. Data Lingo Prediction methods Regression: Predicting a continuous output (stock) Classification: Predicting discrete category outputs. i.e. Yes/Maybe/No
- 42. Data Lingo Data Types Structured: Does it play well in Excel? Unstructured: Raw text (Twitter), audio, video, photos, resumes, etc…