Machine Learning Articles

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Jer Thorp Jer Thorp
Updated on April 09, 2024

How Do Targeted Ads Work? Targeted Ad Advantages & Disadvantages

A lot happens in the seconds between navigating to a web page and seeing the content. And not all of it is good.

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Jacob Vaus and Eli Weiss Jacob Vaus and Eli Weiss
Updated on April 08, 2024

AI Generated Script: How We Made a Movie by an AI Script Writer

We asked an AI to write a screenplay and then filmed what it gave us. Here’s what we learned.

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Manasi Vartak Manasi Vartak
Updated on April 05, 2024

5 Ways to Lessen the Risk of Generative AI

Catalogs and governance structures can help companies minimize the risk of this powerful new tool.

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Eric Siegel Eric Siegel
Updated on April 05, 2024

How to Sell a Machine Learning Project

Never sell “AI.” Instead, pitch operational improvements, with no more than a footnote to mention machine learning as part of the solution.

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Mrinal Tyagi Mrinal Tyagi
Updated on April 02, 2024

Histogram of Oriented Gradients: An Overview

Histogram of oriented gradients (HOG) is a feature descriptor used in computer vision and image processing for object detection. Learn how it works.

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Srik Gorthy Srik Gorthy
Updated on April 01, 2024

Euclidean Distance Explained

Euclidean distance measures the length of the shortest line between two points. It’s commonly used in machine learning algorithms. Learn how to calculate it in Python.

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Rohit Thakur Rohit Thakur
Updated on March 12, 2024

Beginner’s Guide to VGG16 Implementation in Keras

VGG16 is a convolutional neural net architecture that’s used for image recognition. It utilizes 16 layers with weights and is considered one of the best vision model architectures to date.

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Okan Yenigün Okan Yenigün
Updated on March 11, 2024

DBSCAN Clustering Algorithm Demystified

Density-based spatial clustering of applications with noise (DBSCAN) is a clustering algorithm used to define clusters in a data set and identify outliers. Here’s how it works. 

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Sachin Dev Sachin Dev
Updated on March 07, 2024

Understanding Overfitting vs. Underfitting in Machine Learning

Overfitting and underfitting are two problems that can occur when building a machine learning model and can lead to poor performance. Learn what causes them and how to fix it.

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Kevin Li Kevin Li
Updated on March 07, 2024

Here’s How to Build a Culture of Experimentation

Get a team on board and your framework in place, then add a touch of courage to think creatively.

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