View full version: Datascience
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  1. 10. Practicing ‘No Code’ Data Science
  2. 12. The Future of Data Science
  3. 11. Predictive Modelling for Schooling Sector
  4. 12. Introduction to Programming in Stata
  5. 13. Measuring Accuracy for a Multiclass Classification Model
  6. 12. Measuring Accuracy for a Multiclass Classification Model
  7. 10. Predictive Modelling for Schooling Sector
  8. 11. Measuring Accuracy for a Multiclass Classification Model
  9. 7. The Future of Data Science
  10. 8. Predictive Modelling for Schooling Sector
  11. 7. Predictive Modelling for Schooling Sector
  12. 8. The Future of Data Science
  13. 9. Measuring Accuracy for a Multiclass Classification Model
  14. 8. Measuring Accuracy for a Multiclass Classification Model
  15. 3. 88 Resources & Tools to Become a Data Scientist
  16. 4. How to detect spurious correlations, and how to find the real ones
  17. 5. The Future of Data Science
  18. 6. Predictive Modelling for Schooling Sector
  19. 7. Measuring Accuracy for a Multiclass Classification Model
  20. 5. Measuring Accuracy for a Multiclass Classification Model
  21. 3. The Future of Data Science
  22. 4. Measuring Accuracy for a Multiclass Classification Model
  23. 2. Introduction to Programming in Stata
  24. 3. Measuring Accuracy for a Multiclass Classification Model
  25. 1. Introduction to Programming in Stata
  26. 1. What’s New in Data Prep
  27. 2. How to evaluate Data Science models ?
  28. 3. Using Confusion Matrices to Quantify the Cost of Being Wrong
  29. 4. SQL to NoSQL translator
  30. 5. A Comparative Analysis of Top 6 BI and Data Visualization Tools in 2018
  31. 6. Free eBooks from Packt
  32. 8. Open Source automated ETL of web-based data sources
  33. 10. Introduction to Deep Learning
  34. 2. Free eBooks from Packt
  35. 3. What’s New in Data Prep
  36. 6. How to evaluate Data Science models ?
  37. 7. SQL to NoSQL translator
  38. 8. A Comparative Analysis of Top 6 BI and Data Visualization Tools in 2018
  39. 10. A Comparative Analysis of Top 6 BI and Data Visualization Tools in 2018
  40. 6. Hiring and Retaining Scarse Analytics Talent
  41. 7. Open Source automated ETL of web-based data sources
  42. 4. Using Confusion Matrices to Quantify the Cost of Being Wrong
  43. 7. Free eBooks from Packt
  44. 9. Hiring and Retaining Scarse Analytics Talent
  45. 3. A Comparative Analysis of Top 6 BI and Data Visualization Tools in 2018
  46. 5. Using Confusion Matrices to Quantify the Cost of Being Wrong
  47. 6. SQL to NoSQL translator
  48. 7. Analytics Translator – The Most Important New Role in Analytics
  49. 9. Free eBooks from Packt
  50. 11. Open Source automated ETL of web-based data sources
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