Deep Learning Prerequisites: The Numpy Stack in Python

Deep Learning Prerequisites: The Numpy Stack in Python

The Numpy, Scipy, Pandas, and Matplotlib stack: prep for deep learning, machine learning, and artificial intelligence

What you'll learn
Understand supervised machine learning (classification and regression) with real-world examples using Scikit-Learn
Understand and code using the Numpy stack
Make use of Numpy, Scipy, Matplotlib, and Pandas to implement numerical algorithms
Understand the pros and cons of various machine learning models, including Deep Learning, Decision Trees, Random Forest, Linear Regression, Boosting, and More!

Requirements
Understand linear algebra and the Gaussian distribution
Be comfortable with coding in Python
You should already know "why" things like a dot product, matrix inversion, and Gaussian probability distributions are useful and what they can be used for

3.5 hours on-demand video
https://www.udemy.com/deep-learning-prerequisites-the-numpy-stack-in-python/

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