From the course: Rust for Data Engineering
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Exploring life expectancy in a notebook - Rust Tutorial
From the course: Rust for Data Engineering
Exploring life expectancy in a notebook
- [Instructor] Here we have a Google Colab notebook, which is a great place to explore data. One of the nice things about Colab Notebook is it has many features that help you do things at a professional level. So this pro version here, for example, one of the things I can do is I can go to Change runtime, and if I wanted to, I could use GPU or TPU inside, and I also could even use High-RAM if I needed to actually access a larger dataset. What I typically do is create a structure. You can see here I've got Ingest, I have EDA, I might even have a Modeling section. And this allows me to easily navigate or even share sections of the notebook with colleagues. If we look at this right here in this Table of contents, notice how I can easily go to Visualize, or I can go to Ingest, or I can go to Exploratory Data Analysis. What we're going to cover first here is Exploratory Data Analysis, which is getting an idea of what it is…
Contents
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What is Colab?5m 48s
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(Locked)
Using Bard to enhance notebook development6m 7s
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(Locked)
Exploring life expectancy in a notebook6m 53s
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(Locked)
Load a DataFrame with sensitive data1m 36s
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(Locked)
Using MLFlow with Databricks Notebooks5m 26s
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(Locked)
End to End ML with MLFlow and Databricks4m 3s
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(Locked)
Exploring global life expectancy with Polars4m 38s
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