[FreeTutorials.Eu] [UDEMY] End-to-end Machine Learning Time-series analysis - [FTU]

Creation Time	May 27, 2024, 8:46 a.m.
Last Access Time	Sept. 27, 2024, 2:17 a.m.
File Size	1.4 GB
Keywords	FTU FreeTutorials - analysis UDEMY Machine Time-series Learning Eu End-to-end
Total Requests	10
Total Files	59
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2. Get your data/3. Inspect the data.mp4 135.5 MB
6. Wrap up/1. What_s next.mp4(1).mtd 114.0 MB
6. Wrap up/1. What_s next.mp4.mtd 114.0 MB
3. Find your features/4. Write a day-of-year calculator.mp4 95.8 MB
5. Deploy your model/1. Choose your decision criterion.mp4 90.7 MB
1. Introduction/1. Introduction.mp4 85.8 MB
4. Build your model/4. Build the full model and refactor the code.mp4 77.0 MB
4. Build your model/3. Make three-day-out predictions.mp4 71.8 MB
3. Find your features/5. Debug glitch in annual trend.mp4 66.8 MB
4. Build your model/1. Create seasonal model.mp4 66.1 MB
5. Deploy your model/2. Create a Predictor class with tests.mp4 63.3 MB
5. Deploy your model/3. Create a buy_tickets module to answer the question.mp4 51.4 MB
2. Get your data/1. Ask a sharp question.mp4 49.9 MB
3. Find your features/1. How autocorrelation works.mp4 49.8 MB
2. Get your data/7. Replace NaNs with estimates.mp4 46.8 MB
3. Find your features/2. Find the autocorrelation.mp4 46.5 MB
2. Get your data/5. Convert the data to lists.mp4 42.6 MB
2. Get your data/6. Replace missing data with NaNs.mp4 39.0 MB
4. Build your model/2. Explore deseasonalized residuals.mp4 32.2 MB
3. Find your features/3. Inspect the autocorrelation.mp4 22.4 MB
2. Get your data/2. Get weather data.mp4 12.6 MB
2. Get your data/4. Load the data.mp4 11.3 MB
Discuss.FreeTutorials.Us.html 165.7 KB
FreeCoursesOnline.Me.html 108.3 KB
FreeTutorials.Eu.html 102.2 KB
3. Find your features/1. How autocorrelation works.vtt 12.8 KB
2. Get your data/3. Inspect the data.vtt 11.3 KB
3. Find your features/4. Write a day-of-year calculator.vtt 11.1 KB
3. Find your features/5. Debug glitch in annual trend.vtt 8.0 KB
5. Deploy your model/1. Choose your decision criterion.vtt 7.5 KB
4. Build your model/3. Make three-day-out predictions.vtt 7.3 KB
4. Build your model/4. Build the full model and refactor the code.vtt 7.2 KB
2. Get your data/7. Replace NaNs with estimates.vtt 7.0 KB
2. Get your data/5. Convert the data to lists.vtt 6.6 KB
3. Find your features/2. Find the autocorrelation.vtt 6.0 KB
4. Build your model/1. Create seasonal model.vtt 5.9 KB
2. Get your data/6. Replace missing data with NaNs.vtt 5.1 KB
5. Deploy your model/3. Create a buy_tickets module to answer the question.vtt 5.1 KB
5. Deploy your model/2. Create a Predictor class with tests.vtt 4.7 KB
1. Introduction/1. Introduction.vtt 4.6 KB
3. Find your features/3. Inspect the autocorrelation.vtt 4.5 KB
2. Get your data/1. Ask a sharp question.vtt 4.0 KB
4. Build your model/2. Explore deseasonalized residuals.vtt 3.4 KB
2. Get your data/4. Load the data.vtt 2.4 KB
2. Get your data/2. Get weather data.vtt 1.8 KB
[TGx]Downloaded from torrentgalaxy.org.txt 524 bytes
1. Introduction/1.1 fort_lauderdale.csv a copy of the raw data.html 161 bytes
1. Introduction/1.3 predict_weather.py the weather prediction model(1).html 150 bytes
1. Introduction/1.3 predict_weather.py the weather prediction model.html 150 bytes
1. Introduction/1.2 buy_tickets.py the script for deciding whether to buy plane tickets(1).html 146 bytes
1. Introduction/1.2 buy_tickets.py the script for deciding whether to buy plane tickets.html 146 bytes
1. Introduction/1.4 tools.py a couple of tools that might be useful later(1).html 140 bytes
1. Introduction/1.4 tools.py a couple of tools that might be useful later.html 140 bytes
2. Get your data/1.1 Florida State University’s Florida Climate Center.html 113 bytes
2. Get your data/2.1 Florida State University’s Florida Climate Center(1).html 113 bytes
2. Get your data/2.1 Florida State University’s Florida Climate Centerr.html 113 bytes
Torrent Downloaded From GloDls.to.txt 84 bytes
Presented By SaM.txt 33 bytes
2. Get your data/2.1 Florida State University’s Florida Climate Center.html 0 bytes

[FreeTutorials.Eu] [UDEMY] End-to-end Machine Learning Time-series analysis - [FTU]

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