Скачать или смотреть Math Basics required for AI & Machine Learning

🌟 Are you a software engineer looking to break into AI engineering or Machine Learning Engineering but feeling uncertain about the math you need? Let’s discuss the essential math foundations you need to succeed as an AI engineer or ML engineer.
🔢 Here are the three key areas you should focus on:
Calculus:
Learn about derivatives, integrals, and fundamental theorems. I recommend Khan Academy for free courses.
Linear Algebra:
Master matrix operations, vector spaces, and linear transformations. Check out MIT OpenCourseWare for a comprehensive introduction.
Probability and Statistics:
Mathematics for Machine Learning and Data Science Specialization on Coursera is a great free resource.
💻 Don’t let math scare you! It’s simply a tool to help you understand how machines learn. Watch the full video for links to free resources, and start building that math foundation today!
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I give advice for navigating your engineering career journey successfully.


⭐️About me
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Hi, I'm Jean, Founder of Exaltitude. I've been working in tech for the past 20 years as an engineer, an engineering manager, and a team builder. I was the 19th engineer at WhatsApp and worked with Facebook as an Engineering Manager for six years after the $19B acquisition. I'm excited to share the ins and outs of a Software Engineering career based on my experience as a hiring manager for top tech companies.


Credits
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🖼️ All images, graphics, and b-roll videos used in this video were sourced from Canva.

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