Machine learning and AI is extremely easy if you learn the math: My rant.

You just started learning machine learning and AI but wonder why everyone insists on learning the math behind it? To complete projects in ML, you need to know mathematical concepts in AI and machine learning. In this video, we break down why understanding the mathematical foundations is not just important but essential for mastering machine learning. We'll explore why concepts like linear algebra, calculus, probability, and statistics is necessary to learn. Whether you're a beginner or an experienced practitioner, this video will help you appreciate the math that makes machine learning work, and how it can deepen your insights and boost your skills. Let's demystify the math and unlock your full potential in ML!
Stay tuned to stay ahead of the curve in the world of science!
#coding #ai #machinelearning #sciencemajors #datascience #python
More about my learning journey: • Guide to Learning Python
Here's how you can get started with python: • Can you learn python i...
If you want to get started with the first lesson: • Basics of Python | Str...
For workshops I have conducted before: • 5 day python workshop
Erdos Institute boot-camp to learn ML: www.erdosinsti...
Coursera's ML course by Andrew Ng: www.coursera.o...
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.
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