Article Deep Learning Experimentation 
O'Reilly on Data
JULY 28, 2020
In this article, we turn our attention to the process itself: how do you bring a product to market? Without clarity in metrics, it’s impossible to do meaningful experimentation. Experimentation should show you how your customers use your site, and whether a recommendation engine would help the business. Identifying the problem.
O'Reilly on Data
MARCH 19, 2020
Our analysis of ML- and AI-related data from the O’Reilly online learning platform indicates: Unsupervised learning surged in 2019, with usage up by 172%. Deep learning cooled slightly in 2019, slipping 10% relative to 2018, but deep learning still accounted for 22% of all AI/ML usage.
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O'Reilly on Data
OCTOBER 19, 2021
This approach has worked well for software development, so it is reasonable to assume that it could address struggles related to deploying machine learning in production too. Not only is data larger, but models—deep learning models in particular—are much larger than before. However, the concept is quite abstract.
Rocket-Powered Data Science
JULY 6, 2021
1) Automated Narrative Text Generation tools became incredibly good in 2020, being able to create scary good “deep fake” articles. 2) MLOps became the expected norm in machine learning and data science projects. 7) Deep learning (DL) may not be “the one algorithm to dominate all others” after all.
Domino Data Lab
AUGUST 22, 2019
Many thanks to Addison-Wesley Professional for providing the permissions to excerpt “Natural Language Processing” from the book, Deep Learning Illustrated by Krohn , Beyleveld , and Bassens. The excerpt covers how to create word vectors and utilize them as an input into a deep learning model. Introduction.
Data Science and Beyond
DECEMBER 23, 2018
In my opinion it’s more exciting and relevant to everyday life than more hyped data science areas like deep learning. However, I’ve found it hard to apply what I’ve learned about causal inference to my work. I’ve been interested in the area of causal inference in the past few years.
Domino Data Lab
APRIL 7, 2019
A good NLP library will, for example, correctly transform free text sentences into structured features (like cost per hour and is diabetic ), that easily feed into a machine learning (ML) or deep learning (DL) pipeline (like predict monthly cost and classify high risk patients ). Image Credit: Parsa Ghaffari on the Raylien Blog.
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