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? Products based on deep learning can be difficult (or even impossible) to develop; it’s a classic “high return versus high risk” situation, in which it is inherently difficult to calculate return on investment.

Marketing 361

Marketing Experimentation Metrics Testing 361

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. Two functional areas—marketing/advertising/PR and operations/facilities/fleet management—see usage share of about 20%.

Enterprise 307

Enterprise Deep Learning Data Governance Risk 307

O'Reilly on Data

JUNE 18, 2019

As model building become easier, the problem of high-quality data becomes more evident than ever. Even with advances in building robust models, the reality is that noisy data and incomplete data remain the biggest hurdles to effective end-to-end solutions. Data integration and cleaning.

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

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. Deliver use cases to market.

Data Governance 73

Data Governance Strategy Enterprise Machine Learning 73

O'Reilly on Data

MARCH 31, 2020

You’re responsible for the design, the product-market fit, and ultimately for getting the product out the door. That foundation means that you have already shifted the culture and data infrastructure of your company. If you’re just learning to walk, there are ways to speed up your progress. AI doesn’t fit that model.

Management 327

Management Machine Learning Experimentation Metrics 327

Domino Data Lab

MARCH 3, 2019

After a data science conference, our marketing group wanted to follow-up by surveying 300 attendees from industry. Then, when we received 11,400 responses, the next step became obvious to a duo of data scientists on the receiving end of that data collection. The data types used in deep learning are interesting.

Data Science 49

Data Science Deep Learning Machine Learning Modeling 49