Using Python and Excel for Investing in Stock
This course will show you how to use Excel and Python in tandem to pull stock data and related information, calculate returns and establish a portfolio management strategy, predict stock market trends and much more.
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Segment - 01 - Course Overview
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Segment - 02 - What you will learn
Segment - 03 - Pull in Stock Data
Segment - 04 - Pull in more Stock Information
Segment - 05 - Calculate Equity and Returns
Segment - 06 - Calculate Selling Strategy
Segment - 07 - Calculate Total Returns
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Segment - 08 - Pull Historical Stock Data
Segment - 09 - Predict Stocks with Moving Average
Segment - 10 - Visualize Accuracy
Segment - 11 - What is Exponential Smoothing
Segment - 12 - Predict Stocks with Exponential Smoothing
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Segment - 13 - What you will learn
Segment - 14 - Pull Historical Stock Data
Segment - 15 - What is Linear Regression
Segment - 16 - Linear Regression on Stock Data in Excel
Segment - 17 - Check Accuracy of Linear Regression
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Segment - 18 - What you will learn
Segment - 19 - Build Models on the Web
Segment - 20 - What Libraries will we use
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Segment - 21 - Scrape Data via API
Segment - 22 - Define Variables
Segment - 23 - Split Dataset for Training and Testing
Segment - 24 - Build a Linear Regression Model
Segment - 25 - Predict Stock Prices
Segment - 26 - Calculate Model Accuracy
Segment - 27 - Predict to Buy or to Sell
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Segment - 28 - Recurrent Neural Networks
Segment - 29 - Import Stock Data
Segment - 30 - What is Shaping Data
Segment - 31 - Shape Training and Testing Data
Segment - 32 - What is Scaling Data
Segment - 33 - Scale Data for Training
Segment - 34 - What is Keras
Segment - 35 - Build a Keras Model
Segment - 36 - Scale and Shape Data for Testing
Segment - 37 - Test the Model
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