machine learning
‘Tis the Season: Fun with (Decision) Trees
Marina Gandlin | 18 Dec 2019 | Data Science
At Taboola, we work daily on improving our Deep-Learning-based content-recommendation model. We use it to suggest personalized news Read More...
Performing Exploration, Robin-Hood Style
Shaked Zychlinski | 11 Nov 2019 | Machine Learning
Our core business at Taboola is to provide the surfers-of-the-web with personalized content recommendations wherever they might surf. Read More...
Exploiting Multi-Categorical Features Using Deep Interest
Marina Gandlin | 04 Sep 2019 | Data Science
At Taboola, our goal is to predict whether users will click on the ads we present to them. Read More...
Preparing for the Unexpected
Yoel Zeldes | 27 Jan 2019 | Machine Learning
Some of the problems we tackle using machine learning involve categorical features that represent real world objects, such Read More...
Think your Data Different
Zohar Komarovsky and Yoel Zeldes | 21 Jan 2019 | Machine Learning
In the last couple of years deep learning (DL) has become a main enabler for applications in many Read More...
Deep Multi-Task Learning – 3 Lessons Learned
Zohar Komarovsky | 06 Jan 2019 | Data Science
For the past year, my team and I have been working on a personalized user experience in the Read More...
The Story of a Bad Train-Test Split
Yoel Zeldes | 16 Dec 2018 | Data Science
About a year ago we incorporated a new type of feature into one of our models used for Read More...
Predicting Probability Distributions Using Neural Networks
Shaked Zychlinski | 13 Nov 2018 | Data Science
If you’ve been following our tech blog lately, you might have noticed we’re using a special type of Read More...
Title to Image Search for Improved Thumbnail Selection
Gil Levi | 18 Sep 2018 | Data Science
Introduction One of the key creative aspects of an advertisement is choosing the image that will appear alongside Read More...
5 Simple tips for boosting your Jenkins performance
More than one Graph - Code Reuse in TensorFlow
Deep Learning - from Prototype to Production
Neural Networks from a Bayesian Perspective