"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."
Q: What are the state-of-the-art in object recognition and human pose prediction areas? Q: How can we fix the corner cases of our CNN/other computer vision models Q: What is your idea how to improve accuracy close to 100% Q: Why Woven Planet? Why Japan? Do you know Japanese? Other questions about state-of-the-art Background-related questions...
Basic ML things such as loading images from disk, normalizing them, passing them through a pre-trained model, computing embeddings etc.
BERT, OCR, NAtural Language Processing, Deeping Learning.
There were no questions being asked.
Interview questions are fine. But the unprofessionalism left a strong impression on me.
If there were a buh, how would you deal with them
Bagging vs Boosting.Bias Variance tradeoff.
R1: It was a python test. they had given me table in consisting the information about all tests given by students. each entry in data was representing the test score. so I had to group them using pandas and pivot them by subject wise. I wrote the solution anyhow. then interview was based on basic of python and my solution. Round2: After clearing the round1 i got invitation for the r2 i.e NLP round. this time they had given me the dataset of customer problems and sub problems. I had to train a NLP model that can classify the type of problems into different category. I was learning NLP at that stage so I could not perform well in R2. but yeah I learned alot in these process.
Working of Autoencoders, VAEs, GANs etc.
Questions regarding specific machine learning models that I have never heard of before
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