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[] Udemy - Generate and visualize data in Python and MATLAB

  • 收录时间:2020-04-30 15:29:32
  • 文件大小:2GB
  • 下载次数:33
  • 最近下载:2020-12-06 21:31:48
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文件列表

  1. 9. Spatiotemporal structure using forward models/4. Example Simulate human brain (EEG) data.mp4 123MB
  2. 4. Time series signals/6. Dipolar and multipolar chirps.mp4 110MB
  3. 4. Time series signals/3. Smooth transients.mp4 108MB
  4. 5. Time series noise/3. Pink noise (aka 1f aka fractal).mp4 93MB
  5. 9. Spatiotemporal structure using forward models/3. Mixed overlapping forward models.mp4 90MB
  6. 9. Spatiotemporal structure using forward models/2. Forward model 2D sheet.mp4 88MB
  7. 6. Image signals/3. Sine patches and Gabor patches.mp4 86MB
  8. 3. Data distributions/2. Normal and uniform distributions.mp4 83MB
  9. 8. Data clustering in space/2. Clusters in 2D.mp4 83MB
  10. 2. Descriptive statistics and basic visualizations/2. Mean, median, standard deviation, variance.mp4 73MB
  11. 3. Data distributions/4. Poisson distribution.mp4 72MB
  12. 4. Time series signals/4. Repeating sine, square, and triangle waves.mp4 70MB
  13. 7. Image noise/2. Image white noise.mp4 68MB
  14. 6. Image signals/4. Geometric shapes.mp4 67MB
  15. 4. Time series signals/2. Sharp transients.mp4 66MB
  16. 5. Time series noise/5. Multivariable correlated noise.mp4 65MB
  17. 5. Time series noise/2. Seeded reproducible normal and uniform noise.mp4 62MB
  18. 5. Time series noise/4. Brownian noise (aka random walk).mp4 57MB
  19. 7. Image noise/4. Perlin noise in 2D.mp4 56MB
  20. 6. Image signals/5. Rings.mp4 55MB
  21. 6. Image signals/2. Lines and edges.mp4 55MB
  22. 3. Data distributions/7. Cohen's d for separating distributions.mp4 52MB
  23. 7. Image noise/5. Filtered 2D-FFT noise.mp4 51MB
  24. 2. Descriptive statistics and basic visualizations/4. Interquartile range.mp4 51MB
  25. 7. Image noise/3. Checkerboard patterns and noise.mp4 49MB
  26. 1. Introductions/1. Following along in Python, MATLAB, or Octave.mp4 45MB
  27. 3. Data distributions/5. Log-normal distribution.mp4 41MB
  28. 3. Data distributions/6. Measures of distribution quality (SNR and Fano factor).mp4 39MB
  29. 2. Descriptive statistics and basic visualizations/5. Violin plot.mp4 39MB
  30. 3. Data distributions/3. QQ plot.mp4 37MB
  31. 8. Data clustering in space/3. Clusters in N-D.mp4 35MB
  32. 2. Descriptive statistics and basic visualizations/3. Histogram.mp4 34MB
  33. 4. Time series signals/5. Multicomponent oscillators.mp4 34MB
  34. 1. Introductions/5. The importance of visualization.mp4 32MB
  35. 1. Introductions/2. Overall goals of this course.mp4 30MB
  36. 1. Introductions/4. What is signal and what is noise.mp4 26MB
  37. 1. Introductions/3. Why and how to simulate data.mp4 25MB
  38. 9. Spatiotemporal structure using forward models/1.1 genvisdata_forwardModels.zip 4MB
  39. 7. Image noise/1.1 genvisdata_imageNoise.zip 311KB
  40. 2. Descriptive statistics and basic visualizations/1.1 genvisdata_descriptives.zip 230KB
  41. 3. Data distributions/1.1 genvisdata_distributions.zip 199KB
  42. 5. Time series noise/1.1 genvisdata_timeSeriesNoise.zip 163KB
  43. 4. Time series signals/1.1 genvisdata_timeSeriesSignals.zip 152KB
  44. 6. Image signals/1.1 genvisdata_imageSignals.zip 150KB
  45. 8. Data clustering in space/1.1 genvisdata_dataClusters.zip 131KB
  46. 4. Time series signals/3. Smooth transients.srt 25KB
  47. 4. Time series signals/6. Dipolar and multipolar chirps.srt 22KB
  48. 9. Spatiotemporal structure using forward models/4. Example Simulate human brain (EEG) data.srt 22KB
  49. 2. Descriptive statistics and basic visualizations/2. Mean, median, standard deviation, variance.srt 21KB
  50. 3. Data distributions/2. Normal and uniform distributions.srt 20KB
  51. 5. Time series noise/3. Pink noise (aka 1f aka fractal).srt 19KB
  52. 8. Data clustering in space/2. Clusters in 2D.srt 19KB
  53. 6. Image signals/3. Sine patches and Gabor patches.srt 17KB
  54. 9. Spatiotemporal structure using forward models/2. Forward model 2D sheet.srt 16KB
  55. 3. Data distributions/4. Poisson distribution.srt 16KB
  56. 6. Image signals/4. Geometric shapes.srt 16KB
  57. 5. Time series noise/5. Multivariable correlated noise.srt 15KB
  58. 4. Time series signals/2. Sharp transients.srt 15KB
  59. 5. Time series noise/4. Brownian noise (aka random walk).srt 14KB
  60. 6. Image signals/5. Rings.srt 14KB
  61. 6. Image signals/2. Lines and edges.srt 14KB
  62. 4. Time series signals/4. Repeating sine, square, and triangle waves.srt 14KB
  63. 9. Spatiotemporal structure using forward models/3. Mixed overlapping forward models.srt 13KB
  64. 3. Data distributions/7. Cohen's d for separating distributions.srt 13KB
  65. 7. Image noise/2. Image white noise.srt 13KB
  66. 7. Image noise/3. Checkerboard patterns and noise.srt 12KB
  67. 5. Time series noise/2. Seeded reproducible normal and uniform noise.srt 12KB
  68. 3. Data distributions/3. QQ plot.srt 12KB
  69. 3. Data distributions/6. Measures of distribution quality (SNR and Fano factor).srt 12KB
  70. 7. Image noise/4. Perlin noise in 2D.srt 11KB
  71. 2. Descriptive statistics and basic visualizations/5. Violin plot.srt 11KB
  72. 2. Descriptive statistics and basic visualizations/4. Interquartile range.srt 10KB
  73. 3. Data distributions/5. Log-normal distribution.srt 10KB
  74. 1. Introductions/5. The importance of visualization.srt 9KB
  75. 7. Image noise/5. Filtered 2D-FFT noise.srt 9KB
  76. 1. Introductions/1. Following along in Python, MATLAB, or Octave.srt 9KB
  77. 2. Descriptive statistics and basic visualizations/3. Histogram.srt 9KB
  78. 4. Time series signals/5. Multicomponent oscillators.srt 8KB
  79. 1. Introductions/3. Why and how to simulate data.srt 7KB
  80. 1. Introductions/2. Overall goals of this course.srt 6KB
  81. 8. Data clustering in space/3. Clusters in N-D.srt 6KB
  82. 1. Introductions/4. What is signal and what is noise.srt 4KB
  83. 10. Bonus section/1. Bonus lecture.html 3KB
  84. Readme.txt 962B
  85. 9. Spatiotemporal structure using forward models/1. Course materials for this section (reader, MATLAB code, Python code).html 116B
  86. 3. Data distributions/1. Course materials for this section (reader, MATLAB code, Python code).html 76B
  87. 8. Data clustering in space/1. Course materials for this section (reader, MATLAB code, Python code).html 73B
  88. 7. Image noise/1. Course materials for this section (reader, MATLAB code, Python code).html 72B
  89. 6. Image signals/1. Course materials for this section (reader, MATLAB code, Python code).html 70B
  90. 5. Time series noise/1. Course materials for this section (reader, MATLAB code, Python code).html 69B
  91. 2. Descriptive statistics and basic visualizations/1. Course materials for this section (reader, MATLAB code, Python code).html 68B
  92. 4. Time series signals/1. Course materials for this section (reader, MATLAB code, Python code).html 66B
  93. [GigaCourse.com].url 49B