Domino Data Lab

JULY 9, 2019

Wiggins advocated that data scientists find problems that impact the business; re-frame the problem as a machine learning (ML) task; execute on the ML task; and communicate the results back to the business in an impactful way. This post provides distilled highlights, a transcript, and a video of the session. Session Summary.

Data Science 112

Data Science Machine Learning Advertising Modeling 112

Domino Data Lab

JULY 2, 2019

Paco Nathan ‘s latest article covers program synthesis, AutoPandas, model-driven data queries, and more. One of the longer-term trends that we’re seeing with Airflow , and so on, is to externalize graph-based metadata and leverage it beyond the lifecycle of a single SQL query, making our workflows smarter and more robust.

Metadata 105

Metadata Machine Learning Data Science Data-driven 105

Domino Data Lab

SEPTEMBER 9, 2019

This article provides a brief introduction to natural language using spaCy and related libraries in Python. This article and paired Domino project provide a brief introduction to working with natural language (sometimes called “text analytics”) in Python using spaCy and related libraries. Introduction. doc = nlp(text)??

Deep Learning 110

Deep Learning Machine Learning Visualization Data Science 110

Domino Data Lab

JANUARY 6, 2019

In Paco Nathan ‘s latest column, he explores the theme of “learning data science” by diving into education programs, learning materials, educational approaches, as well as perceptions about education. This month, let’s explore learning data science. What are some good learning materials available to the public?

Data Science 56

Data Science Machine Learning Reporting Visualization 56

Domino Data Lab

AUGUST 8, 2019

Meanwhile, many organizations also struggle with “late in the pipeline issues” on model deployment in production and related compliance. Paco Nathan ‘s latest monthly article covers Sci Foo as well as why data science leaders should rethink hiring and training priorities for their data science teams. Introduction. What’s a Foo?

Data Science 71

Data Science Machine Learning Data Governance Statistics 71

O'Reilly on Data

FEBRUARY 18, 2020

O’Reilly online learning contains information about the trends, topics, and issues tech leaders need to watch and explore. Current signals from usage on the O’Reilly online learning platform reveal: Python is preeminent. In programming, Python is preeminent. Still cloud-y, but with a possibility of migration.

Data-driven 335

Data-driven Software Statistics Marketing 335

Edwin Chen

JULY 30, 2012

A couple weeks ago, Facebook launched a link prediction contest on Kaggle, with the goal of recommending missing edges in a social graph. I love investigating social networks , so I dug around a little, and since I did well enough to score one of the coveted prizes, I’ll share my approach here. What does the network look like? Distributions.

Metrics 81

Metrics Testing Machine Learning Modeling 81