Patil Bipin Magan

Perform statistical analysis and fine-tune models using test results. also find available datasets online for training purposes. train and re-train ML systems and models as and when necessary. extend and enrich existing ML frameworks and libraries. develop Machine Learning apps according to customer/client requirements. research, experiment with, and implement suitable ML algorithms and tools. analyze the problem-solving capabilities and use-cases of ML algorithms and rank them by their success probability. also explore and visualize data for better understanding and identify differences in data distribution that could impact model performance when deploying it in real-world scenarios.