Question for experienced Machine Learning Engineers & Data Scientists. 1. How to identify perfect model for data. Either ML or DL model. If it is DL with custom layers how you decide the architecture and identify this is the perfect one ? 2. Till now I do random trials and finalise the model with high accuracy as best model. But how you decide based on understanding your input data ? I’m asking these questions in research perspective.

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How can I get a job as a Machine learning engineer in a good company with a good pay (at least 15 lpa) within 3 months if I am a Software Engineer based in India with 3 yoe? I am a python web developer.

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