Grokking the Machine Learning Interview

Your proven path to success in Machine Learning Interviews – developed by FAANG engineers. Unlock ML loops at top companies with a System Design approach.

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49 Lessons

15h

Updated yesterday

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System design is an important component of any ML interview. Being able to efficiently solve open-ended machine learning problems is a key skill that can set you apart from other engineers and increase the level of seniority at which you’re hired. This course helps you build that skill, and goes over some of the most popularly asked interview problems at big tech companies. You’ll walk step-by-step through solving these problems, focusing in particular on how to design machine learning systems rather than just answering trivia-style questions. Once you’re done with the course, you’ll be able to not just ace the machine learning interview at any tech company, but impress them with your ability to think about systems at a high level. If you have a machine learning or system design interview coming up, you’ll find the course tremendously valuable.

System design is an important component of any ML interview. Being able to efficiently solve open-ended machine learning problem...Show More

TAKEAWAY SKILLS

Machine Learning

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Course Author:

Machine Learning Labs

Developed by MAANG Engineers

Every Educative lesson is designed by a team of ex-MAANG software engineers and PhD computer science educators, and developed in consultation with developers and data scientists working at Meta, Google, and more. Our mission is to get you hands-on with the necessary skills to stay ahead in a constantly changing industry. No video, no fluff. Just interactive, project-based learning with personalized feedback that adapts to your goals and experience.

Trusted by 2.8 million developers working at companies

"The course covered different in-depth use cases within Machine Learning, and opened my mind to multiple considerations I did not have before."

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Software Engineer @ CoffeeSpace

"Educative has been instrumental in accelerating my learning by offering interactive, text-based courses that helped me master complex topics like algorithms, system design, and programming languages."

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Learner

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Frequently Asked Questions

How do I prepare for a machine learning interview?

In order to prepare for a machine learning interview, developers should focus on key topics like algorithms, data preprocessing, model evaluation, and common frameworks. The next step follows: practicing coding problems, reviewing machine learning concepts, and building projects.

What are machine learning interviews?

Machine Learning (ML) interviews judge your knowledge of machine learning frameworks such as TensorFlow and Scikit-learn, and core concepts related to the company’s field. You might also be asked to design an ML system or pipeline while keeping certain specifications in mind. Developers looking to prepare for machine learning interviews should take courses in grokking the machine learning interview.

What are the 4 basics of machine learning?

The four basics of machine learning are as follows:

Data: Models learn patterns and make predictions based on data.
Algorithms: These are the techniques used to process data and learn from it.
Model: A mathematical representation that is used to make predictions.
Training: The process of feeding data into a model to learn patterns.

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