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Machine Learning Engineer Roadmap

Machine learning engineer are the one who carry out modelling and deployment of the ML Model. They are the one with very good knowledge of the software and cloud as well as they possess strong programming skills.

Roadmap to become machine learning Engineer inspired by ml-engineer-roadmap

Disclaimer

This roadmap is created for to keep track of the things i should be doing and learning. Some of the things are taken from blogs and tech talks. The resources here i have listed are random and based on my watchlists.

GIVE A STAR! ⭐

If you like or are using this project to learn or start your journey as ml engineer, please give it a star. Thanks!

Roadmap

Software Engineering

(Languages recommended:- Python and C++)

  1. Data structures and Algorithms
  2. OOP concepts
  3. Software design and Architecture
  4. Design Patterns
  5. Databases and Query Languages
  6. Continous Integration
  7. Testing
  8. Cloud
  9. Containerization (Docker or kubernetes)
  10. Api development

Maths For Machine Learning

  1. Linear Algebra
  2. Calculus
  3. Probability and Statistics

Machine Learning

  1. Supervised Learning
  2. Unsupervised Learning
  3. Numpy
  4. Pandas
  5. Sklearn
  6. Neural Network
  7. Pytorch/Tensorflow (I recommend Pytorch)
  8. MLops
  9. Complete Projects and Resources at The end
  10. Datasets

Software Engineering

Data structures and Algorithms

OOP Concepts

Software design and Architecture

Design Patterns

Databases and Query Languages

Continous Integration

Testing

Cloud

Containerization

Api Development

Maths For Machine Learning

Linear Algebra

Calculus

Probability and Statistics

Machine Learning

Supervised Learning

Unsupervised Learning

Numpy

Pandas

Sklearn

Neural Network

Pytorch

MLops

Projects and Resources

Datasets

Wrap up

If you think this roadmap lacks resources or is incomplete , feel free to message me on Linkedin.

About

this is for myself, development roadmap

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