CIO Business Intelligence

APRIL 19, 2022

Mariya Burrows wanted to make a career change to software development after taking an introductory course on the topic, but the last thing she wanted to do was take out more student loans. Mariya Burrows, software engineer, RealSelf. Mariya Burrows. Despite getting accepted in the midst of the COVID-19 pandemic, Tohni was undeterred.

IT 93

IT Software Cost-Benefit Statistics 93

Domino Data Lab

JANUARY 6, 2019

Lately I’ve been developing curriculum for a client for their new “Intro to Data Science” sequence of courses. What are the foundational parts of our field?”. These two are the fastest-growing courses in the history of Berkeley, now reaching 40% of the campus population. Introduction. This is not a new gig, by any stretch.

Data Science 56

Data Science Machine Learning Reporting Visualization 56

O'Reilly on Data

NOVEMBER 28, 2023

And everyone has opinions about how these language models and art generation programs are going to change the nature of work, usher in the singularity, or perhaps even doom the human race. In enterprises, we’ve seen everything from wholesale adoption to policies that severely restrict or even forbid the use of generative AI. What’s the reality?

Enterprise 269

Enterprise Modeling Testing Reporting 269

DataKitchen

MAY 10, 2021

And the worst part – data errors take the fun out of data science. Remember your first data science courses? They cause people to work long hours at the expense of personal and family time. Data errors also affect careers. Data sources must deliver error-free data on time. Data Observability Component of DataOps.

Testing 214

Testing Manufacturing Data Quality Statistics 214

Domino Data Lab

AUGUST 8, 2019

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. Welcome back to our monthly burst of themespotting and conference summaries. In mid-July I got to attend Sci Foo , held at Google X. Ever heard of it before?

Data Science 71

Data Science Machine Learning Data Governance Statistics 71

Domino Data Lab

MAY 8, 2019

Data science teams need to be using these, as part of their process and workflows – and we’ll get to that point later. Admittedly, throughout large swaths of computer science, reductionism serves quite well. Approaches involving words such as agile and lean have become familiar due to their successes. Let’s look through some antidotes.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

The Unofficial Google Data Science Blog

MARCH 13, 2017

Typically, causal inference in data science is framed in probabilistic terms, where there is statistical uncertainty in the outcomes as well as model uncertainty about the true causal mechanism connecting inputs and outputs. Can we identify what parts of the input the deep network finds noteworthy?

IT 68

IT Visualization Modeling Uncertainty 68