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What are the biggest machine learning trends of 2019 so far, and where are we heading? originally appeared on Quora: the place to gain and share knowledge, empowering people to learn from others and better understand the world.
Answer by Raghav Ramesh, Lead Machine Learning Engineer, DoorDash, on Quora:
The most notable trend right now in machine learning is the rapid growth in machine learning developer tooling and how that changes the process of building, deploying and managing machine learning.
On one end of the spectrum, we have the growth of AutoML like tools which provides powerful machine learning models as a plug and play solution without the need for deep machine learning expertise. This would rapidly bring the power of machine learning to more and more industries.
On the other end of the spectrum, there are numerous tools and products that standardize and provide powerful abstractions for different aspects of machine learning development that lets the data scientists to focus exclusively on their core competencies. Some examples include: tools like MLFlow that handle tracking of different experiment iterations, libraries like Keras that we can quickly use to build state of the art models, developer environments where data scientists can use notebooks on powerful compute machines without having to manage the infrastructure, and automated deployment tools that make it easy to deploy a model.
While currently up to 80% of a data scientist’s time could be spent on auxiliary tasks of data pipelines, model management, or productionization and not the core algorithm, in the near future, with robust tools in place, that is going to be flipped over so we can focus a lot on the core competency of model development.
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