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

Torrent Hash:
0D1C4437F548A5D4CECF6B7DB8874895B95E4E69
Number of Files:
59
Content Size:
1.35GB
Convert On:
2018-11-13
Magnet Link:
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File Name
Size
1. Introduction/1.1 fort_lauderdale.csv a copy of the raw data.html
161B
1. Introduction/1.2 buy_tickets.py the script for deciding whether to buy plane tickets(1).html
146B
1. Introduction/1.2 buy_tickets.py the script for deciding whether to buy plane tickets.html
146B
1. Introduction/1.3 predict_weather.py the weather prediction model(1).html
150B
1. Introduction/1.3 predict_weather.py the weather prediction model.html
150B
1. Introduction/1.4 tools.py a couple of tools that might be useful later(1).html
140B
1. Introduction/1.4 tools.py a couple of tools that might be useful later.html
140B
1. Introduction/1. Introduction.mp4
85.76MB
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1. Introduction/1. Introduction.vtt
4.6KB
2. Get your data/1.1 Florida State University’s Florida Climate Center.html
113B
2. Get your data/1. Ask a sharp question.mp4
49.86MB
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2. Get your data/1. Ask a sharp question.vtt
4.01KB
2. Get your data/2.1 Florida State University’s Florida Climate Center(1).html
113B
2. Get your data/2.1 Florida State University’s Florida Climate Center.html
0B
2. Get your data/2.1 Florida State University’s Florida Climate Centerr.html
113B
2. Get your data/2. Get weather data.mp4
12.62MB
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2. Get your data/2. Get weather data.vtt
1.77KB
2. Get your data/3. Inspect the data.mp4
135.48MB
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2. Get your data/3. Inspect the data.vtt
11.29KB
2. Get your data/4. Load the data.mp4
11.29MB
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2. Get your data/4. Load the data.vtt
2.38KB
2. Get your data/5. Convert the data to lists.mp4
42.62MB
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2. Get your data/5. Convert the data to lists.vtt
6.64KB
2. Get your data/6. Replace missing data with NaNs.mp4
39.02MB
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2. Get your data/6. Replace missing data with NaNs.vtt
5.14KB
2. Get your data/7. Replace NaNs with estimates.mp4
46.81MB
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2. Get your data/7. Replace NaNs with estimates.vtt
6.96KB
3. Find your features/1. How autocorrelation works.mp4
49.82MB
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3. Find your features/1. How autocorrelation works.vtt
12.8KB
3. Find your features/2. Find the autocorrelation.mp4
46.46MB
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3. Find your features/2. Find the autocorrelation.vtt
5.99KB
3. Find your features/3. Inspect the autocorrelation.mp4
22.43MB
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3. Find your features/3. Inspect the autocorrelation.vtt
4.47KB
3. Find your features/4. Write a day-of-year calculator.mp4
95.79MB
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3. Find your features/4. Write a day-of-year calculator.vtt
11.07KB
3. Find your features/5. Debug glitch in annual trend.mp4
66.8MB
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3. Find your features/5. Debug glitch in annual trend.vtt
8KB
4. Build your model/1. Create seasonal model.mp4
66.07MB
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4. Build your model/1. Create seasonal model.vtt
5.87KB
4. Build your model/2. Explore deseasonalized residuals.mp4
32.24MB
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4. Build your model/2. Explore deseasonalized residuals.vtt
3.43KB
4. Build your model/3. Make three-day-out predictions.mp4
71.8MB
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4. Build your model/3. Make three-day-out predictions.vtt
7.34KB
4. Build your model/4. Build the full model and refactor the code.mp4
76.96MB
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4. Build your model/4. Build the full model and refactor the code.vtt
7.23KB
5. Deploy your model/1. Choose your decision criterion.mp4
90.67MB
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5. Deploy your model/1. Choose your decision criterion.vtt
7.49KB
5. Deploy your model/2. Create a Predictor class with tests.mp4
63.35MB
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5. Deploy your model/2. Create a Predictor class with tests.vtt
4.71KB
5. Deploy your model/3. Create a buy_tickets module to answer the question.mp4
51.45MB
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5. Deploy your model/3. Create a buy_tickets module to answer the question.vtt
5.07KB
6. Wrap up/1. What_s next.mp4(1).mtd
114MB
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6. Wrap up/1. What_s next.mp4.mtd
114MB
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