Stock Prices Prediction Project

Зміст курсу

Stock Prices Prediction Project

Stock Prices Prediction Project

Introduction Import Necessary Libraries and Data Preliminary Exploration Let's Plot the Evolution of a Single Stock Add Multiple Stocks to a Single Plot Check the Consistency of the Data Prophet Prophet Fit Predictions Using Prophet Plot the Results

Predictions Using Prophet

Predictions are then made on a DataFrame with a column "ds" containing the dates for which a prediction is to be made. You can get a suitable DataFrame that extends a specified number of days into the future using the helper method Prophet.make_future_dataframe(). By default, it will also include the dates from the history, so we will see the model fit as well.

The predict() method will assign each row in the future a predicted value which it names "yhat". If you pass in historical dates, it will provide an in-sample fit. The forecast object here is a new DataFrame that includes a column "yhat" with the forecast and columns for components and uncertainty intervals.

Завдання

Swipe to start coding

Initialize a DF (with 365 days) where to store predictions using the make_future_dataframe() method;
Make the predictions;
Print the last five rows of this dataset.

Рішення

Mark tasks as Completed

Перейдіть на комп'ютер для реальної практикиПродовжуйте з того місця, де ви зупинились, використовуючи один з наведених нижче варіантів

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Секція 1. Розділ 9

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Зміст курсу

Stock Prices Prediction Project

Stock Prices Prediction Project

Introduction Import Necessary Libraries and Data Preliminary Exploration Let's Plot the Evolution of a Single Stock Add Multiple Stocks to a Single Plot Check the Consistency of the Data Prophet Prophet Fit Predictions Using Prophet Plot the Results

Predictions Using Prophet

Predictions are then made on a DataFrame with a column "ds" containing the dates for which a prediction is to be made. You can get a suitable DataFrame that extends a specified number of days into the future using the helper method Prophet.make_future_dataframe(). By default, it will also include the dates from the history, so we will see the model fit as well.

The predict() method will assign each row in the future a predicted value which it names "yhat". If you pass in historical dates, it will provide an in-sample fit. The forecast object here is a new DataFrame that includes a column "yhat" with the forecast and columns for components and uncertainty intervals.

Завдання

Swipe to start coding

Initialize a DF (with 365 days) where to store predictions using the make_future_dataframe() method;
Make the predictions;
Print the last five rows of this dataset.

Рішення

Mark tasks as Completed

Перейдіть на комп'ютер для реальної практикиПродовжуйте з того місця, де ви зупинились, використовуючи один з наведених нижче варіантів

Все було зрозуміло?

Дякуємо за ваш відгук!

Секція 1. Розділ 9

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