PinnedFrom Notebook to Package“OK, the research part is done, but how should I productionize it?” Says tons of Data Scientists every moment. Up till today, that is still an open question by which DS teams are struggling, and these posts will focus exactly on this topic — How can we make our code…Mlops7 min readMlops7 min read
PinnedAn Intro to Weights and BiasesMy team, the Data Science Research team at Digital Turbine has been working on a new product — the core component of which was an image classification DL model. When the team jumped into this task, our first thought was “What shall we use as our experiment management tool?” For…Wb5 min readWb5 min read
Jul 20, 2020When should we use Unit Testing for Data ScienceThe million dollar question — What are the common use cases for using Unit Testing in a Data Science code pipeline? As you are no doubt aware, the question is not if it is necessary to use unit testing in a DS pipeline, as the answer most definitely is hell yes! But, what to look out for when unit testing? First, What is testing? Testing is defined as a task which…Data Science4 min readData Science4 min read
Aug 11, 2019How to create synergy between MLeap and SparkEver wondered how to develop a ML on Spark and actually make it production grade? Ever asked yourself how to get a ML model quickly to production without Python’s pickle / without “dumping it”? Meet MLeap! MLeap is a common serialization format and execution engine for machine learning pipelines. It…Machine Learning2 min readMachine Learning2 min read