Metrics to Optimize Your Fantasy Football Lineup, Data Labeling for Text Classification, and the Future of AI Design

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2 min readNov 11, 2022

Three Advanced Metrics to Optimize Your Fantasy Football Lineup

Here are three advanced critical metrics to pay attention to when using an optimizer to improve your fantasy football lineup.

Automated Data Labeling for Text Classification

What is data labeling for text classification, why is the manual approach outdated, and why should you look into automation? Get those answers here.

Your Guide to the Evolution and Future of AI Design

In the last decade, we’ve seen the focus of AI design move away from research and development initiatives into real-world applied support. What does the future have in store?

AI Developers: 6 Reasons You Should Care about Better Data Storage

AI projects put diverse demands on infrastructure. Here are six ways storage can help solve data science problems.

What is an AI Data Pipeline? Why Does Storage Matter?

Learn what an AI data pipeline is, why data is the heart of AI, what an AI data pipeline lifecycle looks like, and why the right data platform is so important for AI data pipelines.

Fair and Explainable Machine Learning

In this article, we are going to introduce different techniques that can be applied in order to make our models more fair and explainable.

Our Newest Ally Against Pesky Cockroaches is…AI with Lasers?

Cockroaches should be very afraid, as researchers have developed an AI with lasers to stop them on sight using machine learning.

How Exposing AI to Adversarial Training Can Revolutionize How AI Works

Researchers are working on a way to help artificial intelligence researchers comprehend neural network behavior by using adversarial training.

Upcoming Webinars:

CI/CD for Machine Learning

Wed, Nov 30, 2022, 12:00 PM — 1:00 PM EST

In this talk, you’ll learn how to automatically allocate cloud instances (AWS, Azure, GCP) to train ML models, automatically shut the instance down when training is over, automatically generate reports with graphs and tables in pull/merge requests to summarize your model’s performance using any visualization library, and more.

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