Python has such amazing data science libraries. NumPy is grea | Artificial Intelligence

Python has such amazing data science libraries.

NumPy is great for dealing with input of any shape. Pretty much anything can be thought of as a number, vector, matrix, or tensor. We can transform these, and feed them directly to ML and analytics libraries.

Pandas is great for dealing with tabular data, which happens to be the majority of datasets. Even if something doesn't fit nicely into a table, like a video, we can still store links to them in a Pandas DataFrame.

Matplotlib has powerful yet beautiful visualizations because of the graphs and plots that it produces, it’s extensively used for data visualization. It also provides an object-oriented API, which can be used to embed those plots into applications.

Scikit-Learn is an amazing machine learning library. It has an abundance of algorithms that are extremely easy to use, even if you don't know the underlying math behind them.

Deep Learning has really taken off in the last decade, and TensorFlow, Keras, and PyTorch have really led the way in making it accessible for all to make state of the art neural networks. (Credits: Greg Hogg)

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