Summary: We are entering a new phase in the practice of data science, the'Code-Free' era. Like all major changes this one has not sprung fully grown but the movement is now large enough that its momentum is clear. Here's what you need to know. We are entering a new phase in the practice of data science, the'Code-Free' era. Like all major changes this one has not sprung fully grown but the movement is now large enough that its momentum is clear.
In an industry that is experiencing a steady rate of job creation, data science itself has moved from just a buzzword to a strategic component in organisations. In addition to this, data scientists are increasingly taking on more strategic roles as organisations employ a product-centric view of data. It is a field that promises tremendous job growth and higher earning potential. Our latest research posits 97,000 jobs are available in this buzzing field. On the hiring end, there is a significant overall growth in jobs in the field.
There is currently a lot of talk about automated machine learning. There is also a high level of skepticism. I am here with data scientists Paolo Tamagnini, Simon Schmid and Christian Dietz, to ask a few questions on this topic from their point of view and I found this concept of guided automation quite interesting as well, since it is directly involved in the practice of automated machine learning. Rosaria Silipo: What is automated machine learning? Christian Dietz: Automated machine learning is about building a system, process or application able to automatically create, train and test machine learning models with as little human input as possible.
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