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Machine Learning Interview Questions

"To get a job in machine learning, you must have the programming and mathematical knowledge to create artificial intelligence that is capable of learning new tasks without being explicitly coded. In an interview you may be asked about your experience with pertinent coding languages such as Java and C++ as well as with writing algorithms. The interview will be comprised mainly of technical questions that test your knowledge of the fundamental concepts of machine learning such as data mining and signal processing."

8,197 machine learning interview questions shared by candidates

In the initial discussion round, they have asked questions related to the basics of machine learning and machine learning algorithms. And then they have asked about CNN, RNN, LSTM, different deep learning frameworks like TensorFlow and PyTorch. Questions like what are the updates are there in Tensorflow 2.x compared to 1.x, what is the difference between Tensorflow and Keras. They asked questions related to the projects which I have mentioned in my resume. In coding assessment round, they gave some tasks to perform in a particular deadline.
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Machine Learning Intern

Interviewed at Beneath Analytics

4★
Jul 31, 2020

In the initial discussion round, they have asked questions related to the basics of machine learning and machine learning algorithms. And then they have asked about CNN, RNN, LSTM, different deep learning frameworks like TensorFlow and PyTorch. Questions like what are the updates are there in Tensorflow 2.x compared to 1.x, what is the difference between Tensorflow and Keras. They asked questions related to the projects which I have mentioned in my resume. In coding assessment round, they gave some tasks to perform in a particular deadline.

ML 1. XGBoost usage and applications 2. Genetic vs Bayesian Algorithms Python 1. Advantages of Python 2. Dict comprehension 3. What's a Middleware ? DevOps 1. Lots of AWS questions 2. CI/CD & DDT approaches + automation scripts 3. Nginx - what why & how ? FastAPI 1. Flask is more popular, why use FastAPI ? 2. Importance of Pydantic ? 3. Using routers
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Machine Learning Engineering (MLOps)

Interviewed at Polymerize.io

3.7★
Jan 20, 2022

ML 1. XGBoost usage and applications 2. Genetic vs Bayesian Algorithms Python 1. Advantages of Python 2. Dict comprehension 3. What's a Middleware ? DevOps 1. Lots of AWS questions 2. CI/CD & DDT approaches + automation scripts 3. Nginx - what why & how ? FastAPI 1. Flask is more popular, why use FastAPI ? 2. Importance of Pydantic ? 3. Using routers

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