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Data Science Introduction

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Internal session of Splunk Shanghai for introduction of Data Science

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Data Science Introduction

  1. 1. Data Science Introduction Gang Tao
  2. 2. What is Data Science
  3. 3. Data Science Flow
  4. 4. Statistics and Probability
  5. 5. Admit Gender Dept Freq Admi.ed Male A 512 Rejected Male A 313 Admi.ed Female A 89 Rejected Female A 19 Admi.ed Male B 353 Rejected Male B 207 Admi.ed Female B 17 Rejected Female B 8 Admi.ed Male C 120 Rejected Male C 205 Admi.ed Female C 202 Rejected Female C 391 Admi.ed Male D 138 Rejected Male D 279 Admi.ed Female D 131 Rejected Female D 244 Admi.ed Male E 53 Rejected Male E 138 Admi.ed Female E 94 Rejected Female E 299 Admi.ed Male F 22 Rejected Male F 351 Admi.ed Female F 24 Rejected Female F 317 56% 44% acceptec rejected 65% 35% Men Women
  6. 6. Simpsons Paradox
  7. 7. 45% 16% 18% 11%
  8. 8. Machine Learning
  9. 9. Data Mining or Machine Learning
  10. 10. Key Tools • Classification • Regression • Cluster • Data Reduction
  11. 11. Classification and Regression
  12. 12. Cluster
  13. 13. Data Reduction
  14. 14. Process of ML
  15. 15. Understand Data
  16. 16. Data Scientist
  17. 17. What is Data Scientist • Know which question to ask • Understand the data • Know how to interpret the data • Works in a team
  18. 18. How to become a data scientist ?
  19. 19. Data is Tricky

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