From the course: Machine Learning and AI Foundations: Value Estimations
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Introduction to NumPy, scikit-learn, and pandas
From the course: Machine Learning and AI Foundations: Value Estimations
Introduction to NumPy, scikit-learn, and pandas
- [Instructor] Python is one of the most widely-used programming languages for machine learning. Aside from being a really great and easy-to-use programming language, Python is so popular because many great machine learning libraries are available for it. We are going to use three of the most popular libraries. First, we'll use NumPy. NumPy is a library that allows you to efficiently load and work with large datasets and memory. It's free, open source, and widely used in real systems in Silicon Valley. It's the foundation on which many other machine learning libraries are built. Next, we'll use scikit-learn. Scikit-learn is a very popular machine learning library. Think of it as a Swiss army knife for machine learning. It provides easy-to-use implementations of many of the most popular machine learning algorithms. Finally, we'll also use pandas. Pandas lets you represent your data as a virtual spreadsheet that you can control with code. It has many of the same features you find in…
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