How to BECOME an ML ENGINEER in 2024
Becoming a Machine Learning Engineer can be very overwhelming at first. So many concepts, frameworks, libraries, ...
But don't worry if you are just beginning your journey! I felt (exactly) the same a few years ago, and that's why in this video I want to share with you a list of resources that will help you a lot along the way.
Resources:
💠 𝐅𝐮𝐥𝐥 𝐂𝐨𝐮𝐫𝐬𝐞𝐬
🔸 𝐌𝐚𝐜𝐡𝐢𝐧𝐞 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠 𝐢𝐧 𝐏𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧 𝐛𝐲 DeepLearning.AI
🔗 https://www.coursera.org/learn/introd...
🔸 𝐌𝐚𝐝𝐞 𝐰𝐢𝐭𝐡 𝐌𝐋
🔗 https://madewithml.com/
🔸 𝐓𝐡𝐞 𝐅𝐮𝐥𝐥 𝐒𝐭𝐚𝐜𝐤
🔗 https://fullstackdeeplearning.com/cou...
💠 𝐁𝐥𝐨𝐠𝐬
🔸 Eugene Yan's 𝐁𝐥𝐨𝐠
🔗 https://eugeneyan.com/
🔸 Chip Huyen's 𝐁𝐥𝐨𝐠
🔗 https://huyenchip.com/blog/
🔸 𝐀𝐩𝐩𝐥𝐲𝐢𝐧𝐠𝐌𝐋
🔗 https://applyingml.com/resources/
💠 𝐁𝐨𝐨𝐤𝐬
🔸 𝐃𝐞𝐬𝐢𝐠𝐧𝐢𝐧𝐠 𝐌𝐚𝐜𝐡𝐢𝐧𝐞 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠 𝐒𝐲𝐬𝐭𝐞𝐦𝐬
🔗 https://learning.oreilly.com/library/...
🔸 𝐃𝐞𝐬𝐢𝐠𝐧𝐢𝐧𝐠 𝐃𝐚𝐭𝐚-𝐈𝐧𝐭𝐞𝐧𝐬𝐢𝐯𝐞 𝐀𝐩𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬
🔗 https://learning.oreilly.com/library/...
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If you like this content, you can also follow me here:
💼 LinkedIn - / migueloteropedrido
💻 GitHub - https://github.com/MichaelisTrofficus
🐦 Twitter - https://x.com/MTrofficus
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0:00 Introduction
0:50 MLE Courses
0:54 Machine Learning in Production (Coursera)
3:00 Made With ML (by Goku Mohandas)
5:50 The Full Stack
8:00 MLE Blogs
8:04 Eugene Yan's Blog
9:54 Chip Huyen's Blog
10:48 ApplyingML
11:10 Books
11:23 Designing Data-Intensive Applications
13:17 Designing Machine Learning Systems
14:40 Conclusion
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