From the course: Time Series Analysis and Forecasting with GPT-4o

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Trends, seasonality, cycles, and noise components in time-series data

Trends, seasonality, cycles, and noise components in time-series data - GPT Tutorial

From the course: Time Series Analysis and Forecasting with GPT-4o

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Trends, seasonality, cycles, and noise components in time-series data

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So let's get into ChatGPT website from here. Select model GPT-4o as our forecaster. Remember, what you see on your screen might look different from what is shown here because of the model updates over time, but the key concepts we are learning will still apply. As OpenAI introduces new models, feel free to switch to the latest version. Click the paperclip icon to upload the Bitcoin data set. You can file this data file in the exercise folder. Now let's ask our forecaster. Describe the data set. Explain the columns data types and provide a snapshot of the first few records. Cool. The data set contains historical prices of Bitcoin. There are two columns: the year months of the data entry and the average closing price for that month. Create a line plot for the Bitcoin monthly closed price. Wonderful. The time range starts from September 2014 to April 2024, which is about ten years. Let's think a bit deeper. What does the trend look like over the past ten years? How do prices vary across…

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