Basics of Linear Algebra for AI and ML [with code]: Part 1

Concepts of linear algebra required for AI and machine learning. Here, you will learn the basic mathematical concepts like vectors, matrix and its operations like dot product, determinant, inverse of a matrix, eigen decomposition etc. You will also learn how to solve a system of linear equations and understand the theory of Singular Value Decomposition (SVD). These math concepts are needed to get started with machine learning and learning them early on in your journey will help make the other concepts very simple to understand and implement. In this video, we will code the math from scratch and also use the numpy library. Stay tuned to stay ahead of the curve in the world of science! Timestamps: 0:00 Intro 2:24 Vectors 5:02 Vector operations 7:08 L1 and L2 norm 8:53 Matrix operations 10:42 Matrix Dot product 15:07 Transpose of a matrix 15:48 Determinant of a matrix 22:13 Inverse of a matrix 27:38 Eigen decomposition 32:55 Solve a system of linear equations 34:51 Singular Value Decomposition (SVD) SUBSCRIBE to learn more! ********************************************************************************* My website 🖥️: https://chemcoder.my.canva.site/website-p1 Buy me a coffee ☕️: https://buymeacoffee.com/chemcoder LinkedIn 🤝: www.linkedin.com/in/keerthan-kra268 ********************************************************************************* As an amazon affiliate, I may earn a small commission if you use these links to buy at no extra cost to you. My gear: Beats headphones: https://amzn.to/3ZyZAVj JBL Bluetooth Speaker: https://amzn.to/4ivtulF Logitech Ergonomic Keyboard: https://amzn.to/3OQI49P Logitech Ergonomic Mouse: https://amzn.to/3D6qtrQ Camera Stand: https://amzn.to/3Zoe6Pi Studio light: https://amzn.to/4g6GPzy #coding #ai #machinelearning #sciencemajors #datascience #python Here's the math playlist for AI and ML: https://www.youtube.com/playlist?list=PLRfh8v6mu_F1tC9pX3zML149ddL0TxdCV More about my learning journey: https://www.youtube.com/playlist?list=PLRfh8v6mu_F0UJZf6DKnS2athBG38USXS Here's how you can get started with python: https://youtu.be/BMXKcbMknKU?si=rE4MSMMQgxFMyiXp If you want to get started with the first lesson: https://www.youtube.com/playlist?list=PLRfh8v6mu_F3MrkmQb6ccoNBI5MbmbM_j For workshops I have conducted before: https://www.youtube.com/playlist?list=PLRfh8v6mu_F0W7nD2bIDJUDzrPgGO2QK_ Erdos Institute boot-camp to learn ML: https://www.erdosinstitute.org/boot-camp Coursera's ML course by Andrew Ng: https://www.coursera.org/specializations/machine-learning-introduction? Deep learning book (FREE BOOK): https://www.deeplearningbook.org/ Deep learning book's github page: https://github.com/janishar/mit-deep-learning-book-pdf Elements of statistical learning (Amazon): https://www.amazon.com/Elements-Statistical-Learning-Prediction-Statistics/dp/0387848576 Welcome to ChemCoder. As a computational chemist myself, I had to transition to AI and ML towards the end of my PhD program and I have to admit, it was a lot of learning, making mistakes and late nights. If you are a graduate student, freshman, sophomore or a senior in college and wondering if this field of chemistry and programming is for you, you ARE in the right place! We as chemists or as scientists in general have a very unique position to learn and integrate our coding skills to bring new technology and innovation to the world. The future depends on us and our ability to learn, stay motivated and persistent in this difficult field. Join our community as we strive to get better every day. If you enjoyed this video, consider clicking the LIKE button to help YouTube show this video to others and if you don't want to miss any content from us, consider SUBSCRIBING to the channel. Thank you!