[Tutorialsplanet.NET] Udemy - Simulate, understand, & visualize data like a data scientist
| 文件类型 | 收录时间 | 最后活跃 | 资源热度 | 文件大小 | 文件数量 |
|---|---|---|---|---|---|
| 视频 | 2020-6-22 02:18 | 2024-12-9 15:03 | 188 | 424.44 MB | 41 |
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文件列表
- 1. Introductions/1. Overall goals of this course.mp47.79MB
- 1. Introductions/2. Why and how to simulate data.mp48.9MB
- 1. Introductions/3. What is signal and what is noise.mp48.45MB
- 1. Introductions/4. The importance of visualization.mp411.44MB
- 10. How to become a proactive data scientist/1. Proactive vs. reactive data science.mp46.23MB
- 10. How to become a proactive data scientist/2. Understand data origins and features.mp45.36MB
- 10. How to become a proactive data scientist/3. Write down or sketch the important results.mp48.58MB
- 10. How to become a proactive data scientist/4. Don't give up -- every mistake is a learning opportunity!.mp44.68MB
- 11. Conclusions and how to learn more/1. Conclusions and how to learn more.mp44.92MB
- 2. Descriptive statistics and basic visualizations/2. Mean, median, standard deviation, variance.mp412.33MB
- 2. Descriptive statistics and basic visualizations/3. Interquartile range.mp48.25MB
- 2. Descriptive statistics and basic visualizations/4. Histogram.mp46.39MB
- 2. Descriptive statistics and basic visualizations/5. Violin plot.mp48.71MB
- 3. Data distributions/2. Normal and uniform distributions.mp414.6MB
- 3. Data distributions/3. QQ plot.mp410.85MB
- 3. Data distributions/4. Poisson distribution.mp412.75MB
- 3. Data distributions/5. Log-normal distribution.mp46.34MB
- 3. Data distributions/6. Measures of distribution quality (SNR and Fano factor).mp46.67MB
- 3. Data distributions/7. Cohen's d for separating distributions.mp410.69MB
- 4. Time series signals/2. Sharp transients.mp48.87MB
- 4. Time series signals/3. Smooth transients.mp419.86MB
- 4. Time series signals/4. Repeating sine, square, and triangle waves.mp48.31MB
- 4. Time series signals/5. Multicomponent oscillators.mp46.21MB
- 4. Time series signals/6. Dipolar and multipolar chirps.mp415.43MB
- 5. Time series noise/2. Seeded reproducible normal and uniform noise.mp49.59MB
- 5. Time series noise/3. Pink noise (aka 1f aka fractal).mp412.12MB
- 5. Time series noise/4. Brownian noise (aka random walk).mp48.04MB
- 5. Time series noise/5. Multivariable correlated noise.mp413.22MB
- 6. Image signals/2. Lines and edges.mp46.51MB
- 6. Image signals/3. Sine patches and Gabor patches.mp49.18MB
- 6. Image signals/4. Geometric shapes.mp47.3MB
- 6. Image signals/5. Rings.mp43.82MB
- 7. Image noise/2. Image white noise.mp45.06MB
- 7. Image noise/3. Checkerboard patterns and noise.mp45.15MB
- 7. Image noise/4. Perlin noise in 2D.mp49.93MB
- 7. Image noise/5. Filtered 2D-FFT noise.mp48.48MB
- 8. Data clustering in space/2. Clusters in 2D.mp410.93MB
- 8. Data clustering in space/3. Clusters in N-D.mp48.95MB
- 9. Spatiotemporal structure using forward models/2. Forward model 2D sheet.mp431.41MB
- 9. Spatiotemporal structure using forward models/3. Mixed overlapping forward models.mp418.41MB
- 9. Spatiotemporal structure using forward models/4. Example Simulate human brain (EEG) data.mp433.73MB
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