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Linear Algebra, Statistics and NumPy

391 students enrolled

This course consists of:

3 Tutorials

2 Quizzes

Certificate of Completion

This short 5-part course provides a review of math topics for machine learning (linear algebra and statistics). It also teaches the Python NumPy library, which is used to handle vector and matrices in Python.

Syllabus

Mathematics review (Linear Algebra and Statistics)

Python NumPy library

Introduction to NumPy (follow along)
40 mins
Hands-on Assignment: Data Exploration with NumPyPro
63 mins

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Linear Algebra: Vectors, Matrices and their properties (Quick Review)

Category: Machine Learning

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What prerequisites are required for this course?

Python

How long would this course take to complete?

1 week

What does it cost?

Every tutorial on CommonLounge is available for free, and will always be. We only ask you to come back and contribute and make CommonLounge better for everyone once you are an expert. We offer premium content like quizzes, hands-on projects and certificate of completion as part of our Pro Plan. We also offer one-on-one mentorship and feedback on real-world projects from industry-experts as part of our Plus Plan.

When can I start?

Right now. Enroll in this course and follow it at your own pace. You can also set a reminder above to send the next item to your inbox every week.

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About the contributors

Keshav DhandhaniaMachine Learning @ MIT (2014). DM me for 1-on-1 mentorship (paid).

Bishal LakhaAI and Physics Enthusiast. Robotics Teacher. Previously worked at Coursera.

Krupa SuchakMaster's in Analytics from Georgia Institute of Technology (2018). Bachelor's from MIT (2015).

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