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Udemy - Python for Time Series - Data Analysis and Forecasting

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Added 3 years ago by freecoursewb in Other
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Udemy - Python for Time Series - Data Analysis and Forecasting (Size: 273.2 MB)
  1. ARIMA.mp4 26.7 MB
  1. About this section.html 204.8 B
  1. Checking for seasonality.mp4 14.3 MB
  1. General concepts.mp4 6 MB
  1. Get the data set.html 102.4 B
  1. Pandas Introduction.mp4 23.2 MB
  10. While loops.mp4 3.3 MB
  2. Descriptive statistics introduction & Frequency Tables.mp4 8.3 MB
  2. Dickey - Fuller test for stationarity.mp4 12.1 MB
  2. Gold Prices Data Analysis.mp4 13.9 MB
  2. Pandas Coding Practice.mp4 7.5 MB
  2. Print.mp4 2.8 MB
  3. ARIMA Model.mp4 42.7 MB
  3. Comments.mp4 1.8 MB
  3. Mean - Mode - Median.mp4 6.9 MB
  3. Pandas Coding Practice 2.mp4 8.9 MB
  4. List & List Operations.mp4 5 MB
  4. Mean - Mode - Median Practice.mp4 16.9 MB
  4. Pandas extra codes for time series.mp4 22.4 MB
  5. Inferential statistics introduction.mp4 9.4 MB
  5. Tuples.mp4 1.1 MB
  6. Booleans.mp4 1.6 MB
  6. Hypothesis testing and T-Distribution.mp4 7.1 MB
  7. Hypothesis testing and decision.mp4 4.4 MB
  7. Operators.mp4 3.3 MB
  8. If statements.mp4 4.3 MB
  8. Simple Linear Regression.mp4 9 MB
  9. For loops.mp4 2 MB
  9. Simple Linear Regression practice.mp4 8.4 MB
  Bonus Resources.txt 409.6 B
  Get Bonus Downloads Here.url 204.8 B
  data.csv 15.8 KB
  ▲ 32 total files

Description


Python for Time Series - Data Analysis & Forecasting
https://DevCourseWeb.com

Published 10/2022
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 29 lectures (1h 15m) | Size: 273.3 MB

Learn Python for Time Series - Learn Python libraries for Time Series analysis and forecasting

What you'll learn
Repeat the Statistics and Python fundamentals
Learn building an ARIMA model in Python
Learn the application of Dickey - Fuller test in Python
Learn checking for seasonality in Python

Description
Welcome to the Python for Time Series - Data Analysis & Forecasting course. This course is built for students who wants to learn python applications for time series data sets. This course covers the usage of Python libraries on time series data. There will be both short lectures of statistics and Python fundamentals at the starting of the course in order to remembering the basics. Then the libraries of Python which is used for time series data will be covered. At the end of the course an analysis and forecast is going to be made from gold prices data set for practicing what is learned in the course for one more time. So the course outline is

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