Smart Data Collective

JULY 9, 2023

Collecting Relevant Data for Conversion Rate Optimization Here is some vital data that e-commerce businesses need to collect to improve their conversion rates. Identifying Key Metrics for Conversion Rate Optimization Data collection and analysis are both essential processes for optimizing your conversion rate.

Optimization 74

Optimization Data Analytics Analytics Data-driven 74

Rocket-Powered Data Science

JULY 7, 2019

Chatbots cannot hold long, continuing human interaction. Traditionally they are text-based but audio and pictures can also be used for interaction. They provide more like an FAQ (Frequently Asked Questions) type of an interaction. NLG is a software process that transforms structured data into human-language content.

Internet of Things 157

Internet of Things Machine Learning Manufacturing IoT 157

Cloudera

APRIL 9, 2021

The first blog introduced a mock vehicle manufacturing company, The Electric Car Company (ECC) and focused on Data Collection. The second blog dealt with creating and managing Data Enrichment pipelines. The third video in the series highlighted Reporting and Data Visualization. Data Collection – streaming data.

Machine Learning 98

Machine Learning Forecasting Manufacturing Predictive Analytics 98

Insight

MARCH 12, 2020

In this article, I will discuss the construction of the AIgent, from data collection to model assembly. Data Collection The AIgent leverages book synopses and book metadata. The latter is any type of external data that has been attached to a book? Instead, I built the AIgent. In other words, if 0.1%

Modeling 59

Modeling Metadata Publishing Sales 59

Domino Data Lab

MAY 8, 2019

The lens of reductionism and an overemphasis on engineering becomes an Achilles heel for data science work. Instead, consider a “full stack” tracing from the point of data collection all the way out through inference. ML model interpretability and data visualization. . – back to the structure of the dataset.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

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. Or something.

Data Science 66

Data Science Experimentation Data-driven Machine Learning 66

Domino Data Lab

JUNE 23, 2019

Skomoroch proposes that managing ML projects are challenging for organizations because shipping ML projects requires an experimental culture that fundamentally changes how many companies approach building and shipping software. The biggest time sink is often around data collection, labeling and cleaning.

Management 110

Management Machine Learning Experimentation Metrics 110