Regression forecasting and predicting - Practical Machine Learning Tutorial with Python p.5

TL;DR

In this tutorial, the speaker demonstrates how to use a linear regression algorithm to predict stock prices using unknown data.

Transcript

What's going on Everybody Welcome [to] the fifth machine Learning and Fourth Regression tutorial in This Tutorial? We're Going to be Building on the last one Where We created This Linear Regression Algorithm We Found that it's got great Accuracy and all that And now we're Ready to actually Predict like out Into the Unknown right [so] it Turns out w... Read More

Key Insights

• ❓ Linear regression can be used to predict stock prices using historical data.
• ❓ The accuracy of the algorithm can be measured by comparing predicted values to actual values.
• ⌛ Using unknown data in the algorithm can help make predictions for future time periods.

Summary & Key Takeaways

• The speaker builds on a previous tutorial to create a linear regression algorithm for predicting stock prices.

• The algorithm achieves 96% accuracy and is tested on unknown data.

• The predicted stock prices for the next 30 days are shown on a graph.