Domino Data Lab

JULY 9, 2019

Chris Wiggins , Chief Data Scientist at The New York Times, presented “Data Science at the New York Times” at Rev. Wiggins also indicated that data science, data engineering, and data analysis are different groups at The New York Times. Session Summary. Transcript. Feel free to email me.

Data Science 112

Data Science Machine Learning Advertising Modeling 112

Sisense

APRIL 10, 2020

One of the most-asked questions from aspiring data scientists is: “What is the best language for data science? People looking into data science languages are usually confused about which language they should learn first: R or Python. NLP can be used on written text or speech data. R or Python?”.

Deep Learning 98

Deep Learning Data Science Machine Learning Visualization 98

Domino Data Lab

AUGUST 1, 2021

In this article we cover explainability for black-box models and show how to use different methods from the Skater framework to provide insights into the inner workings of a simple credit scoring neural network model. The interest in interpretation of machine learning has been rapidly accelerating in the last decade.

Modeling 139

Modeling Deep Learning Machine Learning Knowledge Discovery 139

O'Reilly on Data

MARCH 20, 2019

The objective here is to brainstorm on potential security vulnerabilities and defenses in the context of popular, traditional predictive modeling systems, such as linear and tree-based models trained on static data sets. It seems entirely possible to do the same with customer or transactional data.

Modeling 219

Modeling Machine Learning Predictive Modeling Consulting 219

O'Reilly on Data

JUNE 18, 2019

These data sets are often siloed, incomplete, and extremely sparse. Moreover, the domain knowledge, which often is not encoded in the data (nor fully documented), is an integral part of this data (see this article from Forbes). See this article on data integration status for details.

Machine Learning 255

Machine Learning Data Quality Statistics Modeling 255

Cloudera

FEBRUARY 16, 2022

Model interpretability is one of five main components of model governance. The complete list is shown below: Model Lineage . Model Visibility. Model Explainability. Model Interpretability. Model Reproducibility. In this article, we explore model governance, a function of ML Operations (MLOps).

Machine Learning 83

Machine Learning Modeling Metadata Recreation/Entertainment 83

O'Reilly on Data

DECEMBER 12, 2019

Because all ML models make mistakes, everyone who cares about ML should also care about model debugging. [1] 1] This includes C-suite executives, front-line data scientists, and risk, legal, and compliance personnel. Figure 1 illustrates an example adversarial search for an example credit default ML model.

Machine Learning 187

Machine Learning Modeling Testing Risk Management 187

Domino Data Lab

APRIL 21, 2021

In this article, we’ll discuss the challenge organizations face around fraud detection, how machine learning can be used to identify and spot anomalies that the human eye might not catch. deep learning) there is no guaranteed explainability. Knowledge and Data Engineering, IEEE Transactions on, 21, 1263-1284.

Statistics 69

Statistics Machine Learning Modeling Metrics 69