Mastering Time Series Forecasting using Python in 3 Weeks
Mastering Time Series Forecasting using Python in 3 Weeks metadata, size 4071.00 MB, 335 files, category video, indexed at 2026-07-27.
资源标识
Infohashe7e60a20459705e14fc0d9fc2bcb3b63d930fe43
总大小4.0 GB
格式mp4
分类视频
文件数335
发掘时间（北京时间）2026-07-27 19:45:50
最后活跃（北京时间）2026-07-27 19:45:50
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magnet:?xt=urn:btih:e7e60a20459705e14fc0d9fc2bcb3b63d930fe43&dn=Mastering%20Time%20Series%20Forecasting%20using%20Python%20in%203%20Weeks
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文件列表
| 文件名 | 格式 | 大小 |
|---|---|---|
| 6. Forecasting with Confidence Interval and Visualizations in Python.mp4 | mp4 | 120.7 MB |
| TutsNode.com.txt | txt | 63 B |
| 4. Markdown.srt | srt | 24.3 KB |
| 6. Forecasting with Confidence Interval and Visualizations in Python.srt | srt | 24.2 KB |
| 10. List.srt | srt | 20.1 KB |
| 10. Weighted Moving Average in Python.srt | srt | 18.4 KB |
| 3. Download the Resources.html | html | 29 B |
| 15. Arithmetic Operations - part3.srt | srt | 18.1 KB |
| 1. Download the Resources.html | html | 47 B |
| 6. Simple Linear Regression - Python.srt | srt | 15.4 KB |
| 5. Naive Forecasting Model in Python - part 2.srt | srt | 14.5 KB |
| 4. Data Preprocessing.srt | srt | 13.8 KB |
| 3. Data Preprocessing in Python.srt | srt | 13.5 KB |
| 9. Proposition and Stacked Bar, Area Chart.srt | srt | 13.2 KB |
| 1. Multiplicative Model.srt | srt | 13.0 KB |
| 4. Naive Forecasting Model in Python - part 1.srt | srt | 12.9 KB |
| 4. EDA - Quantitative Technique.srt | srt | 12.7 KB |
| 6. Escape and Insert keys.srt | srt | 12.7 KB |
| 7. Random (Uniform & Gaussian Distribution).srt | srt | 12.6 KB |
| 8. Simple Linear Regression - Statsmodels (Python).srt | srt | 12.4 KB |
| 14. Dictionaries.srt | srt | 12.4 KB |
| 1. Additive Model.srt | srt | 12.0 KB |
| 7. Simple Linear Regression - Sklearn (Python).srt | srt | 11.0 KB |
| 8. Data Types.srt | srt | 2.9 KB |
| 2. Intuition of Linear Regression.srt | srt | 10.8 KB |
| 3. Data Analysis in Python.srt | srt | 10.7 KB |
| 12. Exponential Moving Average in Python.srt | srt | 10.7 KB |
| 12. Save Arrays in npy, npz and txt.srt | srt | 10.6 KB |
| 3. Step-1 Trend Model.srt | srt | 10.6 KB |
| 6. Making Data Stationary.srt | srt | 6.7 KB |
| 3. Downloads Data.html | html | 24 B |
| 0 | pad/0 | 43 B |
| 4. Markdown.mp4 | mp4 | 117.6 MB |
| 10. Model Evaluation - Python.srt | srt | 10.5 KB |
| 17. User Defined Functions.srt | srt | 10.2 KB |
| 7. Simple Moving Average in Python.srt | srt | 10.0 KB |
| 8. Simple Moving Average order (q) in Python.srt | srt | 10.0 KB |
| 2. Integrate Google Drive to Colab to Load Data.srt | srt | 10.0 KB |
| 1.1 Python.zip | zip | 9.9 KB |
| 8. Fitted and Forecasting values with AR Model.srt | srt | 9.2 KB |
| 14. Arithmetic Operations - part2.srt | srt | 9.1 KB |
| 6. Fitted values and Forecasting with Multiplicative Model.srt | srt | 9.1 KB |
| 10. Beta Random Distribution.srt | srt | 9.0 KB |
| 5. Print Statements.srt | srt | 9.0 KB |
| 5. ACF & PACF.srt | srt | 8.7 KB |
| 18. Control Statements (if else).srt | srt | 8.5 KB |
| 13. ARIMA.srt | srt | 8.5 KB |
| 3. Setting up Google Colab.srt | srt | 8.2 KB |
| 9. Gamma Random Distribution.srt | srt | 8.1 KB |
| 7. Additive Model Forecasting and Visualizations.srt | srt | 8.1 KB |
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