Roadmap for learning ML Engineering:
🔸 Linear regression
🔸 Logistic regression
🔸 Evaluation metrics
🔸 Docker, web services, cloud
🔸 Model deployment
🔸 Tree-based models
🔸 Neural networks
🔸 Kubernetes
Learn it in this order and you'll be ready for an ML engineering job
@svpino https://t.co/oEBQ9jSFEI is another option in case anyone's interested. The first few chapters deal with the basic math needed to understand prevalent approaches to ML
Mathematics for Machine Learning.
University of Berkeley.
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• Linear Algebra
• Calculus and Optimization
• Probabilities
Download it here: https://t.co/pN19lhLf7y
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"What is a very valuable skill I can learn outside of the main programming languages to help be job ready?"
Git and version control. I can't stress that enough.