[GigaCourse.com] Udemy - Generate and visualize data in Python and MATLAB - 磁力狗

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文档列表

9. Spatiotemporal structure using forward models/4. Example Simulate human brain (EEG) data.mp4 128.5 MB
4. Time series signals/6. Dipolar and multipolar chirps.mp4 115.6 MB
4. Time series signals/3. Smooth transients.mp4 113.5 MB
5. Time series noise/3. Pink noise (aka 1f aka fractal).mp4 97.6 MB
9. Spatiotemporal structure using forward models/3. Mixed overlapping forward models.mp4 94.5 MB
9. Spatiotemporal structure using forward models/2. Forward model 2D sheet.mp4 91.9 MB
6. Image signals/3. Sine patches and Gabor patches.mp4 90.2 MB
3. Data distributions/2. Normal and uniform distributions.mp4 86.8 MB
8. Data clustering in space/2. Clusters in 2D.mp4 86.7 MB
2. Descriptive statistics and basic visualizations/2. Mean, median, standard deviation, variance.mp4 76.5 MB
3. Data distributions/4. Poisson distribution.mp4 75.2 MB
4. Time series signals/4. Repeating sine, square, and triangle waves.mp4 73.5 MB
7. Image noise/2. Image white noise.mp4 71.2 MB
6. Image signals/4. Geometric shapes.mp4 70.2 MB
4. Time series signals/2. Sharp transients.mp4 69.1 MB
5. Time series noise/5. Multivariable correlated noise.mp4 68.4 MB
5. Time series noise/2. Seeded reproducible normal and uniform noise.mp4 64.6 MB
5. Time series noise/4. Brownian noise (aka random walk).mp4 60.1 MB
7. Image noise/4. Perlin noise in 2D.mp4 59.1 MB
6. Image signals/5. Rings.mp4 57.6 MB
6. Image signals/2. Lines and edges.mp4 57.5 MB
3. Data distributions/7. Cohen's d for separating distributions.mp4 54.6 MB
7. Image noise/5. Filtered 2D-FFT noise.mp4 53.6 MB
2. Descriptive statistics and basic visualizations/4. Interquartile range.mp4 53.4 MB
7. Image noise/3. Checkerboard patterns and noise.mp4 51.2 MB
1. Introductions/1. Following along in Python, MATLAB, or Octave.mp4 47.7 MB
3. Data distributions/5. Log-normal distribution.mp4 42.9 MB
3. Data distributions/6. Measures of distribution quality (SNR and Fano factor).mp4 40.8 MB
2. Descriptive statistics and basic visualizations/5. Violin plot.mp4 40.5 MB
3. Data distributions/3. QQ plot.mp4 38.5 MB
8. Data clustering in space/3. Clusters in N-D.mp4 36.8 MB
2. Descriptive statistics and basic visualizations/3. Histogram.mp4 36.0 MB
4. Time series signals/5. Multicomponent oscillators.mp4 35.4 MB
1. Introductions/5. The importance of visualization.mp4 33.9 MB
1. Introductions/2. Overall goals of this course.mp4 31.3 MB
1. Introductions/4. What is signal and what is noise.mp4 27.3 MB
1. Introductions/3. Why and how to simulate data.mp4 26.0 MB
9. Spatiotemporal structure using forward models/1.1 genvisdata_forwardModels.zip 4.2 MB
7. Image noise/1.1 genvisdata_imageNoise.zip 318.2 kB
2. Descriptive statistics and basic visualizations/1.1 genvisdata_descriptives.zip 235.6 kB
3. Data distributions/1.1 genvisdata_distributions.zip 204.0 kB
5. Time series noise/1.1 genvisdata_timeSeriesNoise.zip 166.6 kB
4. Time series signals/1.1 genvisdata_timeSeriesSignals.zip 156.1 kB
6. Image signals/1.1 genvisdata_imageSignals.zip 154.0 kB
8. Data clustering in space/1.1 genvisdata_dataClusters.zip 134.4 kB
4. Time series signals/3. Smooth transients.srt 25.8 kB
4. Time series signals/6. Dipolar and multipolar chirps.srt 22.8 kB
9. Spatiotemporal structure using forward models/4. Example Simulate human brain (EEG) data.srt 22.3 kB
2. Descriptive statistics and basic visualizations/2. Mean, median, standard deviation, variance.srt 21.8 kB
3. Data distributions/2. Normal and uniform distributions.srt 20.9 kB
5. Time series noise/3. Pink noise (aka 1f aka fractal).srt 19.3 kB
8. Data clustering in space/2. Clusters in 2D.srt 19.0 kB
6. Image signals/3. Sine patches and Gabor patches.srt 17.3 kB
9. Spatiotemporal structure using forward models/2. Forward model 2D sheet.srt 16.8 kB
3. Data distributions/4. Poisson distribution.srt 16.3 kB
6. Image signals/4. Geometric shapes.srt 16.2 kB
5. Time series noise/5. Multivariable correlated noise.srt 15.7 kB
4. Time series signals/2. Sharp transients.srt 15.7 kB
5. Time series noise/4. Brownian noise (aka random walk).srt 14.5 kB
6. Image signals/5. Rings.srt 14.4 kB
6. Image signals/2. Lines and edges.srt 14.0 kB
4. Time series signals/4. Repeating sine, square, and triangle waves.srt 14.0 kB
9. Spatiotemporal structure using forward models/3. Mixed overlapping forward models.srt 13.8 kB
3. Data distributions/7. Cohen's d for separating distributions.srt 13.0 kB
7. Image noise/2. Image white noise.srt 12.8 kB
7. Image noise/3. Checkerboard patterns and noise.srt 12.8 kB
5. Time series noise/2. Seeded reproducible normal and uniform noise.srt 12.5 kB
3. Data distributions/3. QQ plot.srt 12.1 kB
3. Data distributions/6. Measures of distribution quality (SNR and Fano factor).srt 11.9 kB
7. Image noise/4. Perlin noise in 2D.srt 11.6 kB
2. Descriptive statistics and basic visualizations/5. Violin plot.srt 11.4 kB
2. Descriptive statistics and basic visualizations/4. Interquartile range.srt 10.6 kB
3. Data distributions/5. Log-normal distribution.srt 10.6 kB
1. Introductions/5. The importance of visualization.srt 9.7 kB
7. Image noise/5. Filtered 2D-FFT noise.srt 9.6 kB
1. Introductions/1. Following along in Python, MATLAB, or Octave.srt 9.3 kB
2. Descriptive statistics and basic visualizations/3. Histogram.srt 9.2 kB
4. Time series signals/5. Multicomponent oscillators.srt 7.7 kB
1. Introductions/3. Why and how to simulate data.srt 7.4 kB
1. Introductions/2. Overall goals of this course.srt 6.4 kB
8. Data clustering in space/3. Clusters in N-D.srt 6.3 kB
1. Introductions/4. What is signal and what is noise.srt 4.4 kB
10. Bonus section/1. Bonus lecture.html 2.8 kB
Readme.txt 962 Bytes
9. Spatiotemporal structure using forward models/1. Course materials for this section (reader, MATLAB code, Python code).html 116 Bytes
3. Data distributions/1. Course materials for this section (reader, MATLAB code, Python code).html 76 Bytes
8. Data clustering in space/1. Course materials for this section (reader, MATLAB code, Python code).html 73 Bytes
7. Image noise/1. Course materials for this section (reader, MATLAB code, Python code).html 72 Bytes
6. Image signals/1. Course materials for this section (reader, MATLAB code, Python code).html 70 Bytes
5. Time series noise/1. Course materials for this section (reader, MATLAB code, Python code).html 69 Bytes
2. Descriptive statistics and basic visualizations/1. Course materials for this section (reader, MATLAB code, Python code).html 68 Bytes
4. Time series signals/1. Course materials for this section (reader, MATLAB code, Python code).html 66 Bytes
[GigaCourse.com].url 49 Bytes

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