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Math 0-1: Linear Algebra for Data Science & Machine Learning

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Math 0-1: Linear Algebra for Data Science & Machine Learning
Math 0 1 Linear Algebra for Data Science Machine Learning

A Casual Guide for Artificial Intelligence, Deep Learning, and Python Programmers

Product Brand: Udemy

Editor's Rating:
4.7

Udemy Coupon Code for Math 0-1: Linear Algebra for Data Science & Machine Learning Course. A Casual Guide for Artificial Intelligence, Deep Learning, and Python Programmers

Created by Lazy Programmer Team, Lazy Programmer Inc. | 20 hours on-demand video course

Linear Algebra for Data Science & Machine Learning Course Overview

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Online Course Math 0-1: Linear Algebra for Data Science & Machine Learning from Udemy

Description for Linear Algebra for Data Science & Machine Learning Course

This Math 0-1: Linear Algebra for Data Science & Machine Learning course will cover systems of linear equations, matrix operations (dot product, inverse, transpose, determinant, trace), low-rank approximations, positive-definiteness and negative-definiteness, and eigenvalues and eigenvectors. It will even include machine learning-focused material you wouldn’t normally see in a regular college course, such as how these concepts apply to GPT-4, and fine-tuning modern neural networks like diffusion models (for generative AI art) and LLMs (Large Language Models) using LoRA.

We will even demonstrate many of the concepts in this Math 0-1: Linear Algebra for Data Science & Machine Learning course using the Python programming language (don’t worry, you don’t need to know Python for this course). In other words, instead of the dry old college version of linear algebra, this course takes just the most practical and impactful topics, and provides you with skills directly applicable to machine learning and data science, so you can start applying them today.

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What You Will Learn

This course is an excellent way to learn Linear Algebra
  • Solve systems of linear equations
  • Understand vectors, matrices, and higher-dimensional tensors
  • Understand dot products, inner products, outer products, matrix multiplication
  • Apply linear algebra in Python
  • Understand matrix inverse, transpose, determinant, trace
  • Understand matrix rank and low-rank approximations (e.g. SVD)
  • Understand eigenvalues and eigenvectors
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Who this course is for

This course is designed for everyone who wants to
  • Anyone who wants to learn linear algebra quickly
  • Students and professionals interested in machine learning and data science but who’ve gotten stuck on the math

Taught by Lazy Programmer Inc.

Josh Smith
Josh Smith

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