Topic
Machine Learning
All Topics
A/B Testing (9) API (1) Artificial Intelligence (31) Automation (6) Automattic (20) best practices (10) Bias in AI (6) Books and Reading (6) Career and Professional Development (14) Causal Inference (1) Communication (14) Conferences and Events (5) Data Analytics (23) Data Discoverability (4) Data Engineering (12) Data Ethics (10) Data Products (1) Data Science (53) Data Speaker Series (4) Data Visualization (23) Deep Learning (3) Distributed Work (8) Diversity and Inclusion (8) Elasticsearch (8) Experimentation (12) Information Retrieval (6) Learning and Education (6) Machine Learning (43) Marketing Analytics (7) Meetup (2) Natural Language Processing (6) Network Analysis (8) Open Source (7) Productivity (10) Python (8) Remote Work (21) Scientific Communication (10) Semantic Search (2) Social Media Analytics (1) Software Engineering (4) Surveys and Research Methods (1) Tech Industry (14) Technology Trends (1) Time Series Analysis (2) Transparency in Data (2) WordPress (21) WordPress.com (1) Work Life Balance (6)
-
Doing the Math on Key Words and Top Level Domains
Boris Gorelike does some analysis on the keywords associated with top level domains.
-
We’re Reading About Simplifying Without Distortion and Adversarial Image Classification
Boris and Carly share what they’ve been reading in the field of data science.
-
Data Speaker Series: Shaun Lindsay on the Data Science of Marketing
Learn how home care company Honor uses data science to aid marketing efforts.
-
We’re Reading About Bias in AI, SpaceX, and More
In this installment, we’ve got links to great reading in the field of data science, courtesy of Yanir, Robert, Demet, and yours truly.
-
Data Speaker Series: Charles Earl on Discriminatory Artificial Intelligence
Charles Earl on identifying and overcoming bias in machine learning.
Data for Breakfast 