How would approach the problem of training dataset imbalance from data and model training perspective?
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describing Multi GPU training process.
would you like to relocate?
1st about LSTM 2nd Precision , Accuracy , f1 score
Describe some ML algorithms? What's overfitting and underfitting and how to avoid them? Given an example problem, how I approach it using ML? describe each stage in detail, including evaluation metrics. Tools I use and why us them?
Linear regression during a tech call, basic ML and medium SQL in HackerRank.
What are the DS applications in oil and gas sector in India?
RAG, Fine tuning, Caching for chat bots
This is out of context, but one question I wrote down was, "What would you tell a CIO to ask a vendor when evaluating an off-the-shelf AI product?"
Write the code for neural network layer used for semantic image classification
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