The AI Coding Gold Rush Ends Where Harness Begins
“Only 30% of software engineering happens on the laptop. The real 70% starts after you commit the code,” says Jyoti
- Published on September 24, 2021
- In Global Tech
How I created An AutoML Library: Ram Seshadri From Google
“And it does it in a few minutes, versus the hours and days other libraries take on a real-world dataset.”
- By Avi Gopani
Ram Seshadri, program manager at Google ML, spoke about his deep learning library, DeepAutoViML, at the DevCon 2021. An expert in Python and SQL, Seshadri’s quantitative background is rich with a bachelors in mechanical engineering and an MBA in finance & economics.
“Build deep learning models for NLP, structured data and images with a single line of code,” described Seshadri. In the talk, he discussed the Deep_AutoViML, its features and a demonstration across different examples.
Deep_AutoViML is an extension of Seshadri’s past open-source libraries; AutoViz, Auto-TS and Auto_ViML. AutoViz is his library to help visualise data sets automatically with a single line of code; Auto_ViML is to automate building pipelines in a single line of code, used especially fo
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Avi Gopani
Avi Gopani is a technology journalist that seeks to analyse industry trends and developments from an interdisciplinary perspective at Analytics India Magazine. Her articles chronicle cultural, political and social stories that are curated with a focus on the evolving technologies of artificial intelligence and data analytics.
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