[Tutorialsplanet.NET] Udemy - Simulate, understand, & visualize data like a data scientist

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    [Tutorialsplanet.NET] Udemy - Simulate, understand, & visualize data like a data scientist

  1. 9. Spatiotemporal structure using forward models/4. Example Simulate human brain (EEG) data.mp4 34.54 MB
  2. 9. Spatiotemporal structure using forward models/2. Forward model 2D sheet.mp4 32.16 MB
  3. 4. Time series signals/3. Smooth transients.mp4 20.33 MB
  4. 9. Spatiotemporal structure using forward models/3. Mixed overlapping forward models.mp4 18.85 MB
  5. 4. Time series signals/6. Dipolar and multipolar chirps.mp4 15.80 MB
  6. 3. Data distributions/2. Normal and uniform distributions.mp4 14.95 MB
  7. 5. Time series noise/5. Multivariable correlated noise.mp4 13.54 MB
  8. 3. Data distributions/4. Poisson distribution.mp4 13.05 MB
  9. 2. Descriptive statistics and basic visualizations/2. Mean, median, standard deviation, variance.mp4 12.63 MB
  10. 5. Time series noise/3. Pink noise (aka 1f aka fractal).mp4 12.41 MB
  11. 1. Introductions/4. The importance of visualization.mp4 11.72 MB
  12. 8. Data clustering in space/2. Clusters in 2D.mp4 11.19 MB
  13. 3. Data distributions/3. QQ plot.mp4 11.11 MB
  14. 3. Data distributions/7. Cohen's d for separating distributions.mp4 10.95 MB
  15. 7. Image noise/4. Perlin noise in 2D.mp4 10.17 MB
  16. 5. Time series noise/2. Seeded reproducible normal and uniform noise.mp4 9.82 MB
  17. 6. Image signals/3. Sine patches and Gabor patches.mp4 9.40 MB
  18. 8. Data clustering in space/3. Clusters in N-D.mp4 9.16 MB
  19. 1. Introductions/2. Why and how to simulate data.mp4 9.12 MB
  20. 4. Time series signals/2. Sharp transients.mp4 9.09 MB
  21. 2. Descriptive statistics and basic visualizations/5. Violin plot.mp4 8.92 MB
  22. 10. How to become a proactive data scientist/3. Write down or sketch the important results.mp4 8.78 MB
  23. 7. Image noise/5. Filtered 2D-FFT noise.mp4 8.68 MB
  24. 1. Introductions/3. What is signal and what is noise.mp4 8.65 MB
  25. 4. Time series signals/4. Repeating sine, square, and triangle waves.mp4 8.50 MB
  26. 2. Descriptive statistics and basic visualizations/3. Interquartile range.mp4 8.44 MB
  27. 5. Time series noise/4. Brownian noise (aka random walk).mp4 8.24 MB
  28. 1. Introductions/1. Overall goals of this course.mp4 7.98 MB
  29. 6. Image signals/4. Geometric shapes.mp4 7.47 MB
  30. 3. Data distributions/6. Measures of distribution quality (SNR and Fano factor).mp4 6.83 MB
  31. 6. Image signals/2. Lines and edges.mp4 6.66 MB
  32. 2. Descriptive statistics and basic visualizations/4. Histogram.mp4 6.54 MB
  33. 3. Data distributions/5. Log-normal distribution.mp4 6.49 MB
  34. 10. How to become a proactive data scientist/1. Proactive vs. reactive data science.mp4 6.38 MB
  35. 4. Time series signals/5. Multicomponent oscillators.mp4 6.36 MB
  36. 10. How to become a proactive data scientist/2. Understand data origins and features.mp4 5.49 MB
  37. 7. Image noise/3. Checkerboard patterns and noise.mp4 5.28 MB
  38. 7. Image noise/2. Image white noise.mp4 5.18 MB
  39. 11. Conclusions and how to learn more/1. Conclusions and how to learn more.mp4 5.04 MB
  40. 10. How to become a proactive data scientist/4. Don't give up -- every mistake is a learning opportunity!.mp4 4.79 MB
  41. 9. Spatiotemporal structure using forward models/1.1 prodata_forwardModels.zip.zip 4.29 MB
  42. 6. Image signals/5. Rings.mp4 3.91 MB
  43. 7. Image noise/1.1 prodata_imageNoise.zip.zip 669 KB
  44. 4. Time series signals/1.1 prodata_TimeSeriesSignals.zip.zip 668 KB
  45. 5. Time series noise/1.1 prodata_TimeSeriesNoise.zip.zip 485 KB
  46. 3. Data distributions/1.1 prodata_dataDistributions.zip.zip 312 KB
  47. 8. Data clustering in space/1.1 prodata_dataClusters.zip.zip 285 KB
  48. 6. Image signals/1.1 prodata_imageSignals.zip.zip 269 KB
  49. 2. Descriptive statistics and basic visualizations/1.1 prodata_descriptiveVisualizations.zip.zip 242 KB
  50. 9. Spatiotemporal structure using forward models/4. Example Simulate human brain (EEG) data.vtt 15 KB