[UDEMY] End-to-end Machine Learning Time-series analysis - [FTU] GloDLS

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name:	[UDEMY] End-to-end Machine Learning Time-series analysis - [FTU] GloDLS
说明: Build a weather predictor using python Created by: Brandon Rohrer Last updated: 4/2018 Language: English Torrent Contains: 58 Files, 6 Folders Course Source: https://www.udemy.com/build-your-own-weather-predictor-end-to-end-data-science/ What you'll learn • Build a weather predictor using python. • Use autocorrelation to build time-series features. • Detect and remove seasonal trends. • Handle missing values. • Download and ingest csv-formatted data. • Handle dates in with a custom python converter. • Evaluate a time-series model's performance. Requirements • It will help if you have used python before. Description Welcome! In this course, we'll walk through every step of making your own weather predictor. We'll find weather data, explore it and get it in order. We'll use the modeling tools of deseasonalization and linear regression to predict temperatures at the beach. We'll use the statistical tools of autoregression and confidence intervals to guide our feature selection and apply our results. And we'll code the whole thing up from scratch in python and organize it to be easy to read and easy to extend. When you're done, you'll have a standalone weather predictor that can estimate high temperatures three days from now. You'll also have hands-on experience solving a real word data science problem from end to end. If you are a professor or a teacher at any level, you are welcome to evaluate the course for free, and I can set your students up with a deep educational discount. Who is the target audience? • Machine learning students and data scientists seeking project-based time series modeling and autocorrelation instruction.
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类别:	Tutorials
语言:	English
总大小:	1.35 GB
哈希信息:	0D1C4437F548A5D4CECF6B7DB8874895B95E4E69
增加:	Prom3th3uS
加入的日期:	2018-11-13 14:56:59
洪流地位:	Torrent Verified

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文件列表:

文件	大小
1. Introduction/1. Introduction.mp4	85.76 MB
1. Introduction/1. Introduction.vtt	4.60 kB
1. Introduction/1.1 fort_lauderdale.csv a copy of the raw data.html	161.00 B
1. Introduction/1.2 buy_tickets.py the script for deciding whether to buy plane tickets(1).html	146.00 B
1. Introduction/1.2 buy_tickets.py the script for deciding whether to buy plane tickets.html	146.00 B
1. Introduction/1.3 predict_weather.py the weather prediction model(1).html	150.00 B
1. Introduction/1.3 predict_weather.py the weather prediction model.html	150.00 B
1. Introduction/1.4 tools.py a couple of tools that might be useful later(1).html	140.00 B
1. Introduction/1.4 tools.py a couple of tools that might be useful later.html	140.00 B
2. Get your data/1. Ask a sharp question.mp4	49.86 MB
2. Get your data/1. Ask a sharp question.vtt	4.01 kB
2. Get your data/1.1 Florida State University’s Florida Climate Center.html	113.00 B
2. Get your data/2. Get weather data.mp4	12.62 MB
2. Get your data/2. Get weather data.vtt	1.77 kB
2. Get your data/2.1 Florida State University’s Florida Climate Center(1).html	113.00 B
2. Get your data/2.1 Florida State University’s Florida Climate Center.html	0.00 B
2. Get your data/2.1 Florida State University’s Florida Climate Centerr.html	113.00 B
2. Get your data/3. Inspect the data.mp4	135.48 MB
2. Get your data/3. Inspect the data.vtt	11.29 kB
2. Get your data/4. Load the data.mp4	11.29 MB
2. Get your data/4. Load the data.vtt	2.38 kB
2. Get your data/5. Convert the data to lists.mp4	42.62 MB
2. Get your data/5. Convert the data to lists.vtt	6.64 kB
2. Get your data/6. Replace missing data with NaNs.mp4	39.02 MB
2. Get your data/6. Replace missing data with NaNs.vtt	5.14 kB
2. Get your data/7. Replace NaNs with estimates.mp4	46.81 MB
2. Get your data/7. Replace NaNs with estimates.vtt	6.96 kB
3. Find your features/1. How autocorrelation works.mp4	49.82 MB
3. Find your features/1. How autocorrelation works.vtt	12.80 kB
3. Find your features/2. Find the autocorrelation.mp4	46.46 MB
3. Find your features/2. Find the autocorrelation.vtt	5.99 kB
3. Find your features/3. Inspect the autocorrelation.mp4	22.43 MB
3. Find your features/3. Inspect the autocorrelation.vtt	4.47 kB
3. Find your features/4. Write a day-of-year calculator.mp4	95.79 MB
3. Find your features/4. Write a day-of-year calculator.vtt	11.07 kB
3. Find your features/5. Debug glitch in annual trend.mp4	66.80 MB
3. Find your features/5. Debug glitch in annual trend.vtt	8.00 kB
4. Build your model/1. Create seasonal model.mp4	66.07 MB
4. Build your model/1. Create seasonal model.vtt	5.87 kB
4. Build your model/2. Explore deseasonalized residuals.mp4	32.24 MB
4. Build your model/2. Explore deseasonalized residuals.vtt	3.43 kB
4. Build your model/3. Make three-day-out predictions.mp4	71.80 MB
4. Build your model/3. Make three-day-out predictions.vtt	7.34 kB
4. Build your model/4. Build the full model and refactor the code.mp4	76.96 MB
4. Build your model/4. Build the full model and refactor the code.vtt	7.23 kB
5. Deploy your model/1. Choose your decision criterion.mp4	90.67 MB
5. Deploy your model/1. Choose your decision criterion.vtt	7.49 kB
5. Deploy your model/2. Create a Predictor class with tests.mp4	63.35 MB
5. Deploy your model/2. Create a Predictor class with tests.vtt	4.71 kB
5. Deploy your model/3. Create a buy_tickets module to answer the question.mp4	51.45 MB
5. Deploy your model/3. Create a buy_tickets module to answer the question.vtt	5.07 kB
6. Wrap up/1. What_s next.mp4(1).mtd	114.00 MB
6. Wrap up/1. What_s next.mp4.mtd	114.00 MB
Discuss.FreeTutorials.Us.html	165.68 kB
FreeCoursesOnline.Me.html	108.30 kB
FreeTutorials.Eu.html	102.23 kB
Presented By SaM.txt	33.00 B
Torrent Downloaded From GloDls.to.txt	84.00 B
[TGx]Downloaded from torrentgalaxy.org.txt	524.00 B

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[UDEMY] End-to-end Machine Learning Time-series analysis - [FTU] GloDLS