Scaling Machine Learning

Original article can be found here (source): Artificial Intelligence on Medium

About the speaker:

Razvan Peteanu’s current role is Lead Architect — Machine Learning at TD Securities. He has 25 years of experience in software development, mostly in the financial industry. His focus over the last several years has been on building scalable machine learning solutions, in the cloud or on premise.

About the talk:

Some of the libraries very commonly taught and used in data science have not been designed for large scale machine learning so scaling up computation can be a challenge, particularly that many courses tend to focus on the algorithms and do not cover ML engineering. On the positive side, there are many ways to address this today and choosing the right one for a given project is an important decision as changing architectures can be expensive. The talk will go through the pros and cons of several approaches to scale up machine learning, including very recent developments.