Ontotext

MAY 26, 2021

Each source covers different aspects of the same real world phenomena or uses different terms for relatively similar things. They identify, match and merge data records referring to the same or a similar entity in multiple datasets and also identify entities that seem to be the same or similar but are not.

Data Quality 87

Data Quality Machine Learning Measurement Metadata 87

Insight

JANUARY 14, 2020

The place was teeming with frenzied bros and the only piece of equipment available was this strange looking thing in the corner. In this post, I will walk through how I built the image classifier for this project using two different implementations of convolutional neural networks (CNNs). What the heck!

Metrics 58

Metrics Optimization Modeling Testing 58

Insight

OCTOBER 25, 2019

In this blog, I’ll illustrate an approach by walking you through my project during my Data Science Fellowship at Insight , followed by a quick discussion pertaining to broader application. In each task’s training phase, a prototype is generated for every class in the task as the center of all labeled training examples from that class.

Snapshot 57

Snapshot Testing Deep Learning Visualization 57

Domino Data Lab

FEBRUARY 20, 2019

Mandel’s previous leadership roles within data engineering, product, and data science teams at multiple companies provides him with a unique perspective when identifying and addressing potential tension points. Introduction: Consider Being Product-Minded. I’ve worked with physicists. “Now

Data Science 76

Data Science Testing Software Uncertainty 76

Insight

SEPTEMBER 20, 2019

In this blog, I’ll describe how this project uses segmentation to detect lesions in an image, and classification to detect whether those lesions are benign or malignant. The loss function used is illustrated in the figure below, with “A” representing the ground truth (manually labeled mask) and “B” representing the model generated mask.

Deep Learning 53

Deep Learning Cost-Benefit Testing Modeling 53

The Unofficial Google Data Science Blog

AUGUST 27, 2019

But given the low probability of violation and wanting to use our rater capacity wisely, this is not an adequate solution — we typically have too few positive labels in uniform samples to achieve an accurate estimate of the prevalence, especially for those sensitive policy verticals. A machine learning classifier serves this task perfectly.

Metrics 98

Metrics Statistics Uncertainty Optimization 98

Sisense

SEPTEMBER 25, 2020

In cases where two or more independent variables are used to predict the value of a dependent variable, it’s called multiple linear regression. Logistic regression is a classification technique that categorizes the dependent variable into multiple categorical classes (i.e., discrete values based on independent variables).

Statistics 98

Statistics Predictive Modeling Modeling Machine Learning 98