Theory of Intelligence
DEEP LEARNING•Sequences And Transformers•Recurrent Neural Networks•1.3 Forecasting Time Series

Introduction

Predicting future values of a series: naive and seasonal baselines you must beat, building windowed datasets for a simple RNN forecaster, and strategies for forecasting several steps ahead.

Introduction

A time series is a sequence of values measured over time: daily website visitors, hourly electricity demand, a patient's heart rate, the number of passengers on a bus line each day. Forecasting means predicting future values from past ones. It's one of the most common business uses of machine learning: planning staff, ordering stock, setting prices.

Think of a weather forecaster. Before using a fancy model, they know the simplest predictions are surprisingly good: "tomorrow will be like today", or "this July will be like last July". Any clever model must beat those simple guesses to be worth using.

Discuss theoretical concepts, mathematical formulas, and architectural foundations.

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