O'Reilly on Data

JULY 28, 2020

Without clarity in metrics, it’s impossible to do meaningful experimentation. AI PMs must ensure that experimentation occurs during three phases of the product lifecycle: Phase 1: Concept During the concept phase, it’s important to determine if it’s even possible for an AI product “ intervention ” to move an upstream business metric.

Marketing 362

Marketing Experimentation Metrics Testing 362

CIO Business Intelligence

JULY 3, 2023

According to a recently leaked Google memo, “The barrier to entry for training and experimentation has dropped from the total output of a major research organization to one person, an evening, and a beefy laptop.”

Management 105

Management Experimentation Modeling Enterprise 105

O'Reilly on Data

MARCH 31, 2020

There may even be someone on your team who built a personalized video recommender before and can help scope and estimate the project requirements using that past experience as a point of reference. It’s difficult to be experimental when your business is built on long-term relationships with customers who often dictate what they want.

Management 332

Management Machine Learning Experimentation Metrics 332

Occam's Razor

APRIL 8, 2013

We are far too enamored with data collection and reporting the standard metrics we love because others love them because someone else said they were nice so many years ago. Sometimes, we escape the clutches of this sub optimal existence and do pick good metrics or engage in simple A/B testing. Online, offline or nonline.

Metrics 156

Metrics KPI Analytics Key Performance Indicator 156

AWS Big Data

JULY 3, 2023

This helps traders determine the potential profitability of a strategy and identify any risks associated with it, enabling them to optimize it for better performance. You can also utilize AWS Data Exchange to select from a range of third-party dataset providers. Load the dataset into Amazon S3. Create an EMR notebook using EMR Studio.

Snapshot 80

Snapshot Data Lake Testing Strategy 80

Cloudera

JUNE 6, 2019

This strategy works well for managing internal chargebacks, limiting the impact of less sophisticated users on more experienced users, and overall encouraging individuals to think about and optimize their jobs and queries now that they have a smaller (but dedicated) cluster. 2) By workload type. 3) By workload priority.

Metadata 88

Metadata Data Lake Optimization Strategy 88

Domino Data Lab

FEBRUARY 4, 2019

We’ll unpack curiosity as a core attribute of effective data science, look at how that informs process for data science (in contrast to Agile, etc.), and dig into details about where science meets rhetoric in data science. That body of work has much to offer the practice of leading data science teams.

Data Science 66

Data Science Experimentation Data-driven Machine Learning 66