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12 Steps You Should Follow to Become a Machine Learning Engineer If you're looking to start a career in machine learning engineering or considering a career switch, you should focus on the following key areas: Mathematics & Statistics: • Linear Algebra, Calculus, and Probability & Statistics: https://lnkd.in/eabKGp.p • OpenIntro Statistics - https://lnkd.in/eQvjgbmB 2-SQL & Databases: https://lnkd.in/ea2DmZ2d 3-Core Concepts of Machine Learning: • Google's ML Crash Course - https://lnkd.in/eT7NiGp6 • Andrew Ng's Coursera ML Course - https://lnkd.in/e964AC7 • Fast.al's Practical Deep Learning- https://course.fast.ai/ 4-Programming Skills (Python & Libraries): • Corey Schafer's Python Tutorials - https://lnkd.in/euyfHHxa • Scikit-learn- https://lnkd.in/eqFhCwXt • TensorFlow - https://lnkd.in/e6RWbe9h • PyTorch - https://lnkd.in/efhPxZPM 5- Model Training & Tuning Techniques: • Kaggle's Intermediate ML- https://lnkd.in/e89AmkzE • Hyperparameter Tuning- https://lnkd.in/ezEnqeG2 6-Advanced Deep Learning Models: • Stanford's CS231n (CNNs) - http://cs231n.github.io/ • Deep Learning Book- https://lnkd.in/e_utEgZM 7-Deployment, Monitoring, & Maintenance: • Docker - https://lnkd.in/esXHzx9k ⚫ Git - https://lnkd.in/esQBFMxS • AWS ML- https://lnkd.in/eZcdQPee ⚫ Azure ML - https://lnkd.in/e5fvmvtk 8-Resume Preparation Soft Skills & Tips: • Resume https://lnkd.in/eP7isRZF • Soft Skills & Tips: https://lnkd.in/e_xE4wdr 9- Machine Learning Projects: • https://lnkd.in/e5kyv3Tv These resources will help you build a strong foundation in machine learning, and develop the skills necessary to excel as a machine learning engineer. Remember, practice is key—so work on projects and apply your knowledge to real-world problems for the best learning experience. If you think I've missed something, please feel free to mention it in the comments section.

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