Forecasting Stock Market with ARIMA Model & Time Series

سرفصل های دوره

Learn how to forecast stock market trends with ARIMA (Autoregressive Integrated Moving Average) model & Time Series

1 - Introduction

1 - Introduction to the Course

2 - Forecasting-Stock-Prices-with-Python.pptx

2 - Table of Contents

3 - Whom This Course is Intended for

2 - Tools IDE and Datasets

4 - Tools IDE and Datasets

3 - Introduction to Stock Market Forecasting

5 - Introduction to Stock Market Forecasting

4 - Calculating Moving Average

6 - Calculating Moving Average

6 - calculatingmovingaverage.zip

5 - ARIMA Model Calculation

7 - ARIMA Model Calculation

7 - arimamodelcalculation.zip

6 - Internal External Factors That Can Impact Stock Market

8 - Internal External Factors That Can Impact Stock Market

7 - Setting Up Google Colab

9 - Google Colab IDE.txt

9 - Setting Up Google Colab

8 - Finding Downloading Dataset From Kaggle

10 - Finding Downloading Dataset From Kaggle

10 - Kaggle.txt

9 - Project Forecasting Stock Market Trend with ARIMA Model

11 - StockMarketDataset.zip

11 - Uploading Dataset to Google Colab

12 - Quick Overview of Stock Market Datset

13 - Cleaning Dataset by Removing Missing Duplicate Values

14 - Analysing Visualising Average Highest Lowest Stock Price Per Year

15 - Analysing Visualising Average Volume

16 - Finding Correlation Between Volume Price Change

17 - Calculating 100 Days Moving Average

18 - Analysing Visualising Volatility

19 - Auto Correlation Function Partial Auto Correlation Function

20 - Forecasting with ARIMA Performing Residual Analysis

10 - Forecasting Model Evaluation

21 - Calculating Mean Absolute Error Mean Squared Error Root Mean Squared Error

11 - Conclusion Summary

22 - Conclusion Summary

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تولید کننده: Udemy