1 posts
Introduction to Deep Learning

Sebastian Raschka made 170 videos on deep learning, and you can watch all of the lessons now: I just sat down this morning and organized all deep learning related videos I recorded in 2021. I am sure this will be a useful reference for my future self, but I am also hoping it might be useful for one or the other person out there. It’s split into 19 lessons over...

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Spatula, a Python library for maintainable web scraping

This looks promising: While it is often easy, and tempting, to write a scraper as a dirty one-off script, spatula makes an attempt to provide an easy framework that most scrapers fit within without additional overhead. This reflects the reality that many scraper projects start small but grow quickly, so reaching for a heavyweight tool from the start often does not seem practical. The initial overhead imposed by the framework...

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Generate a color analysis by uploading an image

Mel Dollison and Liza Daly made a fun interactive that lets you upload an image, and it spits out a vintage-looking color analysis a la Vanderpoel: This generator is based on the works of Emily Noyes Vanderpoel (1842-1939), who hoped her original color analyses would inspire others to study “whatever originals may be at hand in books, shops, private houses, or museums.” We hope you are similarly inspired by her...

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✚ How to Make Line Charts in Python, with Pandas and Matplotlib

The chart type can be used to show patterns over time and relationships between variables. This is a comprehensive introduction to making them using two common libraries. Read More

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Altair for visualization in Python

Vega-Lite is a grammar for interactive graphics primarily used for analysis. Altair is a visualization library in Python that is based on this grammar. With Altair, you can spend more time understanding your data and its meaning. Altair’s API is simple, friendly and consistent and built on top of the powerful Vega-Lite visualization grammar. This elegant simplicity produces beautiful and effective visualizations with a minimal amount of code. Jim Vallandingham...

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Extracting NBA player movement data

NBA basketball teams have tracking systems installed in their arenas called SportVu, essentially a system of cameras pointed at the court to track player movements. Some of that data is browsable through the NBA site, but there's understandably no direct download link. However, there is an API. Savvas Tjortjoglou wrote a thorough tutorial on how to grab data via the API and plot it Python. This will be fun. Tags:...

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