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آموزش تحلیل سریهای زمانی در Python 2020

دانلود Udemy Time Series Analysis in Python 2020

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عنوان اصلی : Time Series Analysis in Python 2020

این مجموعه آموزش ویدیویی محصول موسسه آموزشی Udemy است که بر روی 1 حلقه دیسک به همراه اسلایدهای مدرس ارائه شده و به مدت زمان 7 ساعت و 18 دقیقه در اختیار علاقه مندان قرار می گیرد.

در ادامه با برخی از سرفصل های درسی این مجموعه آموزش آشنا می شویم :


Introduction :
What does the course cover?

Setting Up the Environment :
Setting up the environment - Do not skip, please!
Why Python and Jupyter?
Installing Anaconda
Jupyter Dashboard - Part 1
Jupyter Dashboard - Part 2
Installing the Necessary Packages
Installing Packages - Exercise
Installing Packages - Exercise Solution

Introduction to Time Series in Python :
Introduction to Time-Series Data
Introduction to Time Series Data
3 questions
Notation for Time Series Data
Notation for Time Series Data
1 question
Peculiarities of Time Series Data
Peculiarities of Time Series Data
2 questions
Loading the Data
Loading the Data
1 question
Examining the Data
Examining the Data
2 questions
Plotting the Data
Plotting the Data
1 question
The QQ Plot
The QQ Plot
1 question

Creating a Time Series Object in Python :
Transforming String inputs into DateTime Values
Transforming String inputs into DateTime Values
1 question
Using Date as an Index
Using Dates as an Index
1 question
Setting the Frequency
Setting the Frequency
1 question
Filling Missing Values
Filling Missing Values
1 question
Adding and Removing Columns in a Data Frame
Adding and Removing Columns in a Data Frame
1 question
Splitting Up the Data
Splitting Up the Data
1 question
Appendix: Updating the Dataset

Working with Time Series in Python :
White Noise
White Noise
2 questions
Random Walk
Random Walk
1 question
Stationarity
Stationarity
1 question
Determining Weak Form Stationarity
Determining Weak Form Stationarity
1 question
Seasonality
Seasonality
1 question
Correlation Between Past and Present Values
Correlation Between Past and Present Values
1 question
The Autocorrelation Function (ACF)
The Autocorrelation Function (ACF)
1 question
The Partial Autocorrelation Function (PACF)
The Partial Autocorrelation Function (PACF)
1 question

Picking the Correct Model :
Picking the Correct Model
Picking the Correct Model
1 question

Modeling Autoregression: The AR Model :
The Autoregressive (AR) Model
The Autoregressive (AR) Model
1 question
Examining the ACF and PACF of Prices
Examining the ACF and PACF of Prices
1 question
Fitting an AR(1) Model for Index Prices
Fitting an AR(1) Model for Index Prices
1 question
Fitting Higher-Lag AR Models for Prices
Fitting Higher-Lag AR Models for Prices
1 question
Using Returns Instead of Prices
Using Returns Instead of Prices
1 question
Examining the ACF and PACF of Returns
Examining the ACF and PACF of Returns
1 question
Fitting an AR(1) Model for Index Returns
Fitting an AR(1) Model for Index Returns
1 question
Fitting Higher-Lag AR Models for Returns
Fitting Higher-Lag AR Models for Returns
1 question
Normalizing Values
Normalizing Values
1 question
Model Selection for Normalized Returns (AR)
Model Selection for Normalized Returns
1 question
Examining the AR Model Residuals
Examining the AR Model Residuals
1 question
Unexpected Shocks from Past Periods

Adjusting to Shocks: The MA Model :
The Moving Average (MA) Model
The Moving Average (MA) Model
1 question
Fitting an MA(1) Model for Returns
Fitting an MA(1) Model for Returns
1 question
Fitting Higher-Lag MA Models for Returns
Fitting Higher-Lag MA Models for Returns
1 question
Examining the MA Model Residuals for Returns
Examining the MA Model Residuals for Returns
1 question
Model Selection for Normalized Returns (MA)
Model Selection for Normalized Returns (MA)
1 question
Fitting an MA(1) Model for Prices
Fitting an MA(1) Model for Prices
1 question
Past Values and Past Errors

Past Values and Past Errors: The ARMA Model :
The Autoregressive Moving Average (ARMA) Model
The Autoregressive Moving Average (ARMA) Model
1 question
Fitting a Simple ARMA Model for Returns
Fitting a Simple ARMA Model for Returns
1 question
Fitting a Higher-Lag ARMA Model for Returns - Part 1
Fitting a Higher-Lag ARMA Model for Returns - Part 2
Fitting a Higher-Lag ARMA Model for Returns - Part 3
Fitting a Higher-Lag ARMA Model for Returns - Part 3
1 question
Examining the ARMA Model Residuals of Returns
Examining the ARMA Model Residuals of Returns
1 question
ARMA for Prices
ARMA for Prices
1 question
ARMA Models and Non-Stationary Data

Modeling Non-Stationary Data: The ARIMA Model :
The Autoregressive Integrated Moving Average (ARIMA) Model
The Autoregressive Integrated Moving Average (ARIMA) Model
1 question
Fitting a Simple ARIMA Model for Prices
Fitting a Simple ARIMA Model for Prices
1 question
Fitting a Higher-Lag ARIMA Model for Prices - Part 1
Fitting a Higher-Lag ARIMA Model for Prices - Part 2
Fitting a Higher-Lag ARIMA Model for Prices - Part 2
1 question
Higher Levels of Integration
Higher Levels of Integration
1 question
Using ARIMA Models for Returns
Using ARIMA Models for Returns
1 question
Outside Factors and the ARIMAX Model
Outside Factors and the ARIMAX Model
1 question
Seasonal Models - SARIMAX
Predicting Stability

Measuring Volatility: The ARCH Model :
The Autoregressive Conditional Heteroscedasticity (ARCH) Model
The ARCH Model
1 question
Volatility
Volatility
1 question
A More Detailed Look of the ARCH Model
A More Detailed Look of the ARCH Model
1 question
The arch_model Method
The arch_model Method
1 question
The Simple ARCH Model
The SImple ARCH Model
1 question
Higher-Lag ARCH Models
An ARMA Equivalent of the ARCH Model

An ARMA Equivalent of the ARCH: The GARCH Model :
The Generalized Autoregressive Conditional Heteroskedasticity (GARCH) Model
The GARCH Model
1 question
The ARMA and the GARCH
The ARMA and the GARCH
1 question
The Simple GARCH Model
The Simple GARCH Model
1 question
Higher-Lag GARCH Models
Higher-LAg GARCH Models
1 question
An Alternative to the Model Selection Process

Auto ARIMA :
Auto ARIMA
Preparing Python for Model Selection
The Default Best Fit
Basic Auto ARIMA Arguments
Advanced Auto ARIMA Arguments
The Goal Behind Modelling

Forecasting :
Introduction to Forecasting
Simple Forecasting Returns with AR and MA
Intermediate ("MAX" Model) Forecasting
Advanced (Seasonal) Forecasting
Auto ARIMA Forecasting
Pitfalls of Forecasting
Forecasting Volatility
Forecasting Appendix: Multivariate Forecasting

Business Case :
Business Case - A Look Into the Automobile Industry

مشخصات این مجموعه :
زبان آموزش ها انگلیسی روان و ساده
دارای آموزشهای ویدیویی و دسته بندی شده
ارائه شده بر روی 1 حلقه دیسک به همراه اسلایدهای مدرس
مدت زمان آموزش 7 ساعت و 18 دقیقه !
محصول موسسه آموزشی Udemy