Sisense

APRIL 10, 2020

We’ll actually do this later in this article. These support a wide array of uses, such as data analysis, manipulation, visualizations, and machine learning (ML) modeling. Using XG-Boost to model the text data resulted in an almost identical score for Python and R. R libraries.

Deep Learning 98

Deep Learning Data Science Machine Learning Visualization 98

IBM Big Data Hub

JULY 6, 2023

Other challenges include communicating results to non-technical stakeholders, ensuring data security, enabling efficient collaboration between data scientists and data engineers, and determining appropriate key performance indicator (KPI) metrics. Python is the most common programming language used in machine learning.

Machine Learning 62

Machine Learning Data Science Statistics Deep Learning 62

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] This article is meant to be a short, relatively technical primer on what model debugging is, what you should know about it, and the basics of how to debug models in practice.

Machine Learning 191

Machine Learning Modeling Testing Risk Management 191

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 84

Machine Learning Modeling Metadata Recreation/Entertainment 84

Smarten

APRIL 19, 2024

In this article, we will discuss the current state of AI in analytics, as well as the future of this burgeoning industry and how it can be applied to analytics to simplify and clarify results and to make analytics easier for businesses and business users to leverage.

Analytics 57

Analytics Predictive Modeling KPI Machine Learning 57

Domino Data Lab

AUGUST 22, 2019

Many thanks to Addison-Wesley Professional for providing the permissions to excerpt “Natural Language Processing” from the book, Deep Learning Illustrated by Krohn , Beyleveld , and Bassens. The excerpt covers how to create word vectors and utilize them as an input into a deep learning model.

Deep Learning 111

Deep Learning Modeling Metrics Testing 111

Rocket-Powered Data Science

JULY 6, 2021

1) Automated Narrative Text Generation tools became incredibly good in 2020, being able to create scary good “deep fake” articles. The old models were not able to predict very well based on the previous year’s data since the previous year seemed like 100 years ago in “data years”. And the goodness doesn’t stop there.

Data-driven 279

Data-driven Machine Learning IoT Deep Learning 279