O'Reilly on Data

MARCH 18, 2020

Supervised learning is the most popular ML technique among mature AI adopters, while deep learning is the most popular technique among organizations that are still evaluating AI. By contrast, AI adopters are about one-third more likely to cite problems with missing or inconsistent data.

Enterprise 307

Enterprise Deep Learning Data Governance Risk 307

O'Reilly on Data

MARCH 24, 2020

Beyond the autonomous driving example described, the “garbage in” side of the equation can take many forms—for example, incorrectly entered data, poorly packaged data, and data collected incorrectly, more of which we’ll address below. The model and the data specification become more important than the code.

Machine Learning 343

Machine Learning Statistics Data Quality Modeling 343

O'Reilly on Data

JUNE 18, 2019

“AI starts with ‘good’ data” is a statement that receives wide agreement from data scientists, analysts, and business owners. As model building become easier, the problem of high-quality data becomes more evident than ever. As model building become easier, the problem of high-quality data becomes more evident than ever.

Machine Learning 255

Machine Learning Data Quality Statistics Modeling 255

CIO Business Intelligence

APRIL 25, 2022

It’s a fast growing and lucrative career path, with data scientists reporting an average salary of $122,550 per year , according to Glassdoor. Here are the top 15 data science boot camps to help you launch a career in data science, according to reviews and data collected from Switchup. Data Science Dojo.

Data Science 145

Data Science Machine Learning Deep Learning Statistics 145

O'Reilly on Data

JULY 28, 2020

These measures are commonly referred to as guardrail metrics , and they ensure that the product analytics aren’t giving decision-makers the wrong signal about what’s actually important to the business. It’s generally accepted that, during a typical product development cycle, 80% of a data scientist’s time is spent in feature engineering.

Marketing 361

Marketing Experimentation Metrics Testing 361

Cloudera

OCTOBER 1, 2022

While the word “data” has been common since the 1940s, managing data’s growth, current use, and regulation is a relatively new frontier. . Governments and enterprises are working hard today to figure out the structures and regulations needed around data collection and use. It can’t do that anymore.

Data Governance 73

Data Governance Strategy Enterprise Machine Learning 73

O'Reilly on Data

MARCH 31, 2020

Many consumer internet companies invest heavily in analytics infrastructure, instrumenting their online product experience to measure and improve user retention. It turns out that type of data infrastructure is also the foundation needed for building AI products. If you can’t walk, you’re unlikely to run.

Management 327

Management Machine Learning Experimentation Metrics 327