IBM Big Data Hub

AUGUST 11, 2023

Machine learning engineers take massive datasets and use statistical methods to create algorithms that are trained to find patterns and uncover key insights in data mining projects. These insights can help drive decisions in business, and advance the design and testing of applications.

Data Science 56

Data Science Machine Learning Cost-Benefit Deep Learning 56

Cloudera

FEBRUARY 16, 2022

We can think of model lineage as the specific combination of data and transformations on that data that create a model. This maps to the data collection, data engineering, model tuning and model training stages of the data science lifecycle. Figure 04: Applied Machine Learning Prototypes (AMPs).

Machine Learning 81

Machine Learning Modeling Metadata Recreation/Entertainment 81

O'Reilly on Data

MARCH 31, 2020

The model outputs produced by the same code will vary with changes to things like the size of the training data (number of labeled examples), network training parameters, and training run time. This has serious implications for software testing, versioning, deployment, and other core development processes.

Management 332

Management Machine Learning Experimentation Metrics 332

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. Machine learning model interpretability. . – back to the structure of the dataset.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

Domino Data Lab

MARCH 3, 2019

This month, the theme is not specifically about conference summaries; rather, it’s about a set of follow-up surveys from Strata Data attendees. We had big surprises at several turns and have subsequently published a series of reports. Evolving Data Infrastructure: Tools and Best Practices for Advanced Analytics and AI (Jan 2019).

Data Science 49

Data Science Deep Learning Machine Learning Modeling 49

Insight

JANUARY 14, 2020

In short, I was faced with two major difficulties regarding data collection: I didn’t have nearly enough images, and the images I did have were not representative of a realistic gym environment. And the winner is… Both implementations of our gym equipment classifier achieved 99% accuracy on the test set.

Metrics 58

Metrics Optimization Modeling Testing 58

Occam's Razor

OCTOBER 12, 2017

The first two are from editions of my newsletter, The Marketing – Analytics Intersect (it goes out weekly, and is now my primary publishing channel, sign up!). When you go to the interview, the hiring company will proceed to ask questions that test your competency in the listed job requirements. Intro to Machine Learning.

Marketing 136

Marketing Analytics Machine Learning Strategy 136