How I learned Machine Learning by predicting tomorrow's weather

In this video, we’ll dive into machine learning using Python and Google Colab.

We'll start by getting a weather dataset from NOAA, then clean it up by removing columns with too many missing values, filling in gaps, and filtering out unnecessary information.

After that, we’ll build a model using Ridge Regression to predict precipitation for a specific day based on the weather from the day before. We’ll also look at how different settings in the model affect the results.

In the next video, we’ll add more predictors like rolling and expanding averages and try out other types of regression to see which works best!

Dataset:
https://github.com/jsilryan/Datasets/blob/main/Nairobi%20data.csv

I'll share the code once I go through all parts of the notebook.

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Видео How I learned Machine Learning by predicting tomorrow's weather канала Jsil Tech