Math 0-1: Linear Algebra for Data Science & Machine Learning
What you'll learn
- 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
Requirements
- Firm understanding of high school math
Description
Common scenario: You try to get into machine learning and data science, but there's SO MUCH MATH.
Either you never studied this math, or you studied it so long ago you've forgotten it all.
What do you do?
Well my friends, that is why I created this course.
Linear Algebra is one of the most important math prerequisites for machine learning. It's required to understand probability and statistics, which form the foundation of data science.
The "data" in data science is represented using matrices and vectors, which are the central objects of study in this course.
If you want to do machine learning beyond just copying library code from blogs and tutorials, you must know linear algebra.
In a normal STEM college program, linear algebra is split into multiple semester-long courses.
Luckily, I've refined these teachings into just the essentials, so that you can learn everything you need to know on the scale of hours instead of semesters.
This 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 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.
Are you ready?
Let's go!
Suggested prerequisites:
Firm understanding of high school math (functions, algebra, trigonometry)
Who this course is for:
- 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
Instructors
- 4.7 Instructor Rating
- 60,411 Reviews
- 209,466 Students
- 21 Courses
The Lazy Programmer is a seasoned online educator with an unwavering passion for sharing knowledge. With over 10 years of experience, he has revolutionized the field of data science and machine learning by captivating audiences worldwide through his comprehensive courses and tutorials.
Equipped with a multidisciplinary background, the Lazy Programmer holds a remarkable duo of master's degrees. His first foray into academia led him to pursue computer engineering, with a specialized focus on machine learning and pattern recognition. Undeterred by boundaries, he then ventured into the realm of statistics, exploring its applications in financial engineering.
Recognized as a trailblazer in his field, the Lazy Programmer quickly embraced the power of deep learning when it was still in its infancy. As one of the pioneers, he fearlessly embarked on instructing one of the first-ever online courses on deep learning, catapulting him to the forefront of the industry.
Beyond the realm of education, the Lazy Programmer possesses invaluable hands-on experience that has shaped his expertise. His ventures into online advertising and digital media have yielded astounding results, propelling click-through rates and conversion rates to new heights and boosting revenues by millions of dollars at the companies he's worked for. As a full-stack software engineer, he boasts intimate familiarity with an array of backend and web technologies, including Python, Ruby on Rails, C++, Scala, PHP, Javascript, SQL, big data, Spark, and Redis.
While his achievements in the field of data science and machine learning are awe-inspiring, the Lazy Programmer's intellectual curiosity extends far beyond these domains. His fervor for knowledge leads him to explore diverse fields such as drug discovery, bioinformatics, and algorithmic trading. Embracing the challenges and intricacies of these subjects, he strives to unravel their potential and contribute to their development.
With an unwavering commitment to his students and a penchant for simplifying complex concepts, the Lazy Programmer stands as an influential figure in the realm of online education. Through his courses in data science, machine learning, deep learning, and artificial intelligence, he empowers aspiring learners to navigate the intricate landscapes of these disciplines with confidence.
As an author, mentor, and innovator, the Lazy Programmer leaves an indelible mark on the world of data science, machine learning, and beyond. With his ability to demystify the most intricate concepts, he continues to shape the next generation of data scientists and inspires countless individuals to embark on their own intellectual journeys.
- 4.6 Instructor Rating
- 164,281 Reviews
- 557,134 Students
- 38 Courses
The Lazy Programmer is a seasoned online educator with an unwavering passion for sharing knowledge. With over 10 years of experience, he has revolutionized the field of data science and machine learning by captivating audiences worldwide through his comprehensive courses and tutorials.
Equipped with a multidisciplinary background, the Lazy Programmer holds a remarkable duo of master's degrees. His first foray into academia led him to pursue computer engineering, with a specialized focus on machine learning and pattern recognition. Undeterred by boundaries, he then ventured into the realm of statistics, exploring its applications in financial engineering.
Recognized as a trailblazer in his field, the Lazy Programmer quickly embraced the power of deep learning when it was still in its infancy. As one of the pioneers, he fearlessly embarked on instructing one of the first-ever online courses on deep learning, catapulting him to the forefront of the industry.
Beyond the realm of education, the Lazy Programmer possesses invaluable hands-on experience that has shaped his expertise. His ventures into online advertising and digital media have yielded astounding results, propelling click-through rates and conversion rates to new heights and boosting revenues by millions of dollars at the companies he's worked for. As a full-stack software engineer, he boasts intimate familiarity with an array of backend and web technologies, including Python, Ruby on Rails, C++, Scala, PHP, Javascript, SQL, big data, Spark, and Redis.
While his achievements in the field of data science and machine learning are awe-inspiring, the Lazy Programmer's intellectual curiosity extends far beyond these domains. His fervor for knowledge leads him to explore diverse fields such as drug discovery, bioinformatics, and algorithmic trading. Embracing the challenges and intricacies of these subjects, he strives to unravel their potential and contribute to their development.
With an unwavering commitment to his students and a penchant for simplifying complex concepts, the Lazy Programmer stands as an influential figure in the realm of online education. Through his courses in data science, machine learning, deep learning, and artificial intelligence, he empowers aspiring learners to navigate the intricate landscapes of these disciplines with confidence.
As an author, mentor, and innovator, the Lazy Programmer leaves an indelible mark on the world of data science, machine learning, and beyond. With his ability to demystify the most intricate concepts, he continues to shape the next generation of data scientists and inspires countless individuals to embark on their own intellectual journeys.