Machine Learning is a diverse field covering a wide territory and has impacted many verticals. It is able to tackle tasks in language and image processing, anomaly detection, credit scoring sentiment analysis, forecasting alongside dozens of other downstream tasks. A proficient developer, in this line of work; has to be able to draw, borrow, and steal from many adjacent fields such as mathematics, statistics, programming, and most importantly common sense. I for one have drawn tremendous benefits from myriad of tools available to break down complex tasks into smaller more manageable components. It turns out that developing and training a model only takes a small fraction of the project duration. The bulk of the time and resources are spent on data acquisition, preparation, hyperparameter tuning, optimization, and model deployment. I have been successful in building a systematic knowledge base that has helped my team to tackle some common yet tough challenges. Read More

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