Subject archive for "machine," page 2

In this Data Science Popup session, Danny Lange, VP of AI and Machine Learning at Unity Technologies, gives an inside look at practical applications and challenges of AI in enterprises such as Unity, Netflix, Uber, and elsewhere.

This week, Domino’s Chief Data Scientist, Eduardo Ariño de la Rubia, presented a webinar: Machine Learning at Scale with Amazon's X1 Instance. If you missed the live webinar or would like to watch it again, you can find a recording below:

Note: Please be advised that direct access to containers via SSH has been deprecated for Domino versions above 4.x. Indirect SSH access via Workspace terminals (e.g. JupyterLab, VSCode etc.) is still available in all Domino releases.

At Data By The Bay in May, we saw a great talk by Netflix's Justin Basilico: Recommendations for Building Machine Learning Software. Justin describes some principles for effectively developing machine learning algorithms and integrating them into software products.

In this recorded webcast, Daniel Emaasit introduces model-based machine learning and related concepts, practices and tools such as Bayes' Theorem, probabilistic programming, and RStan.

This blog post follows my journey from traditional statistical modeling to Machine Learning (ML) and introduces a new paradigm of ML called Model-Based Machine Learning (Bishop, 2013). Model-Based Machine Learning may be of particular interest to statisticians, engineers, or related professionals looking to implement machine learning in their research or practice.