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. If an attacker can receive many predictions from your model API or other endpoint (website, app, etc.),

Modeling 226

Modeling Machine Learning Predictive Modeling Consulting 226

O'Reilly on Data

JUNE 18, 2019

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). In this post, we shed some light on various efforts toward generating data for machine learning (ML) models. See this article on data integration status for details.

Machine Learning 264

Machine Learning Data Quality Statistics Modeling 264

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. Nowadays text data is huge, so Deep Learning also comes into the picture. R libraries. Both languages are user-friendly and easy to implement.

Deep Learning 98

Deep Learning Data Science Machine Learning Visualization 98

IBM Big Data Hub

JULY 6, 2023

Python is the most common programming language used in machine learning. Machine learning and deep learning are both subsets of AI. Deep learning teaches computers to process data the way the human brain does. Deep learning algorithms are neural networks modeled after the human brain.

Machine Learning 54

Machine Learning Data Science Statistics Deep Learning 54

Domino Data Lab

JULY 28, 2021

In this article, we will provide an overview of the three overlapping components of data science, the importance of communication and collaboration, and how the Domino Data Lab MLOps platform can help improve the speed and efficiency of your team. All models are not made equal. After cleaning, the data is now ready for processing.

Data Science 110

Data Science Statistics Predictive Analytics Recreation/Entertainment 110

Smart Data Collective

SEPTEMBER 19, 2019

The Machine Learning Technology That Drives TTS. A couple of years ago, Medium contributor Utkarsh Saxena penned a great article on speech synthesis technology with machine learning. They talked about two very important machine learning approaches: Parametric TTS and Concatenative TTS.

Machine Learning 83

Machine Learning Technology Deep Learning Predictive Modeling 83

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

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 197

Machine Learning Modeling Testing Risk Management 197

IBM Big Data Hub

MAY 17, 2024

Poorly run implementations of traditional or generative AI technology in commerce—such as deploying deep learning models trained on inadequate or inappropriate data—lead to bad experiences that alienate both consumers and businesses.

B2B 64

B2B Interactive Optimization Forecasting 64

Domino Data Lab

JULY 9, 2019

Diving into examples of building and deploying ML models at The New York Times including the descriptive topic modeling-oriented Readerscope (audience insights engine), a prediction model regarding who was likely to subscribe/cancel their subscription, as well as prescriptive example via recommendations of highly curated editorial content.

Data Science 112

Data Science Machine Learning Advertising Modeling 112

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. A drawback of the ML approach is that there for certain algorithms (e.g.

Statistics 69

Statistics Machine Learning Modeling Metrics 69

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