How To Learn Math for Machine Learning FAST (Even With Zero Math Background)

I dropped out of high school and managed to became an Applied Scientist at Amazon by self-learning math (and other ML skills). In this video I'll show you exactly how I did it, sharing the resources and study techniques that worked for me, along with practical advice on what math you actually need (and don't need) to break into machine learning and data science. ---------------------------------------- 📬 Sign up for my newsletter for access to a FREE 80+ page e-book on how to get your first data science job (learning resources, project ideas, LinkedIn checklist, and more): https://www.gratitudedriven.com/subscribe 💬 If you'd like to chat with me 1:1, you can book a call here: https://topmate.io/marina_wyss ☕ If you'd like to support my work, you can buy me a coffee (thank you!): https://ko-fi.com/marinawyss 📝 Transcript: https://medium.com/@gratitudedriven/how-to-learn-math-for-machine-learning-fast-even-with-zero-math-background-159757833c3a ---------------------------------------- ⏰ Timestamps 00:00 Introduction 00:35 Do you even need to learn math to work in ML? 02:22 What math you should learn to work in ML? 05:05 Learning resources and roadmap 07:48 Getting clear on your motivation for learning 08:41 Tips on how to study math for ML effectively 11:18 Do I recommend prioritizing math as a beginner? ---------------------------------------- 🎥 Other videos you might like: Beginner to (Employed) Data Scientist in 2025: Complete Roadmap - Skills, Projects, CV, Interviews https://www.youtube.com/watch?v=uakGF0DP-mk&t=16s Study Without Suffering: How to Stay Competitive in Tech (or Any Industry) While Working Full-Time https://www.youtube.com/watch?v=ZWYc68ejzVc&t=6s ---------------------------------------- ✍️ Learning Resources DeepLearning.AI Coursera Specialization: https://imp.i384100.net/gOOn1B Imperial College London Coursera Specialization: https://imp.i384100.net/LKDXbV The Manga Guide to Linear Algebra: https://amzn.to/3DEZC6y The Manga Guide to Calculus: https://amzn.to/40rz2ad The Manga Guide to Statistics: https://amzn.to/4j1smqc Practical Statistics for Data Scientists: https://amzn.to/49EqG1A Mathematics for Machine Learning book: https://mml-book.github.io/ Essence of Linear Algebra playlist: https://www.youtube.com/watch?v=fNk_zzaMoSs&list=PLZHQObOWTQDPD3MizzM2xVFitgF8hE_ab Essence of Calculus playlist: https://www.youtube.com/watch?v=WUvTyaaNkzM&list=PLZHQObOWTQDMsr9K-rj53DwVRMYO3t5Yr StatQuest: https://www.youtube.com/@statquest Quick note, many of these links are affiliate links, meaning I'll make a small commission if you purchase them (at no additional cost to you!) ---------------------------------------- 🦫 About me I am an Applied Scientist (basically, a blend of Data Scientist/Machine Learning Engineer) at Twitch/Amazon. Outside of my full-time job I'm a technical mentor at a machine learning bootcamp, and a 1:1 career coach for people looking to break into the field, with a focus on those from non-traditional backgrounds. I’m also a Certified Personal Trainer, always busy with too many interests, and really, deeply happy with my life. I hope to be able to help others achieve these things, too. Instagram: / gratitudedriven ---------------------------------------- ✉️ Contact Leave me a comment here on YouTube! Business email: [email protected] ---------------------------------------- ⚖️ Disclaimer The views and opinions expressed in this video are my own and do not reflect the official policy or position of Twitch/Amazon or any other company I have worked for. All advice and insights shared here are based on my personal experiences and should be considered as such. #machinelearning #mathforml #datascience