Data analysis, Data set, Data, Memetics, Hate speech, Statistics

Hateful Memes: Phase 2 Hosted By Facebook

On Oct 31, 2020
@ylecun shared
RT @facebookai: Tomorrow's the last day for the Hateful Memes challenge! See how well your model identifies multimodal hate speech in Internet memes. Submit here: https://t.co/61UUYcfrto
Open

Detecting hateful content presents a unique challenge in memes, where multiple data modalities need to be analyzed together. Facebook is calling on researchers around the world to help identify which memes contain offensive content in violation of its policies.

www.drivendata.org
On Oct 31, 2020
@ylecun shared
RT @facebookai: Tomorrow's the last day for the Hateful Memes challenge! See how well your model identifies multimodal hate speech in Internet memes. Submit here: https://t.co/61UUYcfrto
Open

Hateful Memes: Phase 2 Hosted By Facebook

Hateful Memes: Phase 2 Hosted By Facebook

Detecting hateful content presents a unique challenge in memes, where multiple data modalities need to be analyzed together. Facebook is calling on researchers around the world to help ...

Hateful Memes

Hateful Memes

Detecting hateful content presents a unique challenge in memes, where multiple data modalities need to be analyzed together. Facebook is calling on researchers around the world to help ...

Facebook Offers $50K For AI That Can Detect Hateful Memes

Facebook Offers $50K For AI That Can Detect Hateful Memes

Facebook's created a dataset of 10,000 ‘hateful’ memes and is offering prizes totaling $100,000 for developers who can use it to detect hate speech in memes.

Hateful Memes Challenge and data set for research on harmful multimodal content

Hateful Memes Challenge and data set for research on harmful multimodal content

We’re launching the Hateful Memes Challenge, an online competition with a $100K total prize pool, and sharing a data set designed specifically to help AI researchers develop new systems to ...

A Crash Course for Journalists In Classifying Text with Machine Learning

A Crash Course for Journalists In Classifying Text with Machine Learning

When journalists ask their audience for help, success creates a whole new problem: what do you do with thousands of tips? Or what do you do with thousands of textual descriptions of … ...

All the President’s Memes

All the President’s Memes

It’s disorienting enough that the president communicates using internet memes. It’s even stranger to consider that his policies might work the same way.

Using TensorFlow with IBM Event Streams (Kafka + Machine Learning = Awesome)

Using TensorFlow with IBM Event Streams (Kafka + Machine Learning = Awesome)

In this post, I want to explain how to get started creating machine learning applications using the data you have on Kafka topics. I've written a sample app, with examples of how you can ...

Python Machine Learning Tutorial, Scikit-Learn: Wine Snob Edition

Python Machine Learning Tutorial, Scikit-Learn: Wine Snob Edition

Step-by-step Python machine learning tutorial for building a model from start to finish using Scikit-Learn. We'll have some fun and predict wine quality!

Scalable Active Learning for Autonomous Driving: A Practical Implementation and A/B Test

Scalable Active Learning for Autonomous Driving: A Practical Implementation and A/B Test

Learn how our scalable active learning approach streamlines training data selection for autonomous driving DNNs.

What Is Overfitting?

What Is Overfitting?

When you train a neural network, you have to avoid overfitting. Overfitting is an issue within machine learning and statistics where a model learns the patterns of a training dataset too ...

Category Archives for "Data Science Tutorials"

Category Archives for "Data Science Tutorials"

Originally developed for financial time series such as daily stock market prices, the robust and flexible data structures in pandas can be applied to time series data in any domain, ...

Do people “cheat” by overfitting test data

Do people “cheat” by overfitting test data

NLP in 2020 is dominated by papers which report small improvements in state-of-art. I suspect that a lot of these improvements are due to overfitting test data, not to genuine scientific ...

How to Train to the Test Set in Machine Learning

How to Train to the Test Set in Machine Learning

Training to the test set is a type of overfitting where a model is prepared that intentionally achieves good performance on a given test set at the expense of increased generalization ...

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Application of Data Mining Techniques to Predict Students Placement in to Departments Getaneh Berie Tarekegn MSC, Department of Computer Science Faculty of Engineering and Technology Assosa ...

Accuracy Too Good to Be True? Beware the Muddy Label!

Accuracy Too Good to Be True? Beware the Muddy Label!

In one of my earliest data science projects I predicted adoption of a software product based on columnar *phone home* data with a single binary label: Adopter My very first model achieved ...

It’s not all Pepes and trollfaces — memes can be a force for good

It’s not all Pepes and trollfaces — memes can be a force for good

How the ‘emotional contagion’ of memes makes them the internet’s moral conscience