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PACT-3D, a deep learning algorithm for pneumoperitoneum detection in abdominal CT scans

Flipboard

The model is trained on abdominal scans from Far Eastern Memorial Hospital (January 2012–December 2021) and evaluated using a simulated test set (14,039 scans) and a prospective test set (6351 scans) collected from the same center between December 2022 and May 2023.

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3 Ways to Learn Data Science and Get a Job in 2024

Towards AI

All the way back in 2012, Harvard Business Review said that Data Science was the sexiest job of the 21st century and recently followed up with an updated version of their article. Okay, let’s get started! So, before we look at how to learn data science, we need to know: what really is a data scientist?

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DataRobot Recognized as a Leader in Forrester New Wave for Automation-Focused Machine Learning Solutions

DataRobot

In 2012, DataRobot co-founders Jeremy Achin and Tom de Godoy recognized the profound impact that AI and machine learning could have on organizations, but that there wouldn’t be enough data scientists to meet the demand.

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Promote pipelines in a multi-environment setup using Amazon SageMaker Model Registry, HashiCorp Terraform, GitHub, and Jenkins CI/CD

AWS Machine Learning Blog

We build a model to predict the severity (benign or malignant) of a mammographic mass lesion trained with the XGBoost algorithm using the publicly available UCI Mammography Mass dataset and deploy it using the MLOps framework. The full instructions with code are available in the GitHub repository.

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Engineering the First Fitbit: The Inside Story

Hacker News

The algorithms that determine Fitbit’s count Part of Fitbit’s challenge of getting from prototype to shippable product was software development. Instead, the device’s algorithms needed to determine what a step was and what was a different kind of motion—say, someone scratching their nose. Road noise was another big issue.

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Introducing a blog series: The key trio of software development, project management, and data science

Data Science Dojo

Fast-forward; year: 2012. Thus, one thing led to another, and soon enough, I was practicing algorithms and data-structures, learning about the basic “trouble-trio” of web-development–i.e., But our instructor couldn’t really teach us about interpretive methods, ethnography, and qualitative interviewing etc., And I did, but grudgingly.

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Causal Inference Python Implementation

Towards AI

This historical sales data covers sales information from 2010–02–05 to 2012–11–01. The main goal of the algorithm is to infer the expected effect a given intervention (or any action) had on some response variable by analyzing differences between expected and observed time series data.

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