Getting Started with PyTorch, Creating Word Clouds from Text, Flyte for MLOps, and Jobs
In this free-to-download guide, you’ll get everything you need to know to get started with PyTorch for machine learning and deep learning!
Read on for a quick example of how you can create attractive word clouds from text by using open-source tools.
Get started with Flyte, an open-source, container-native, structured programming, and distributed processing platform for MLOps.
In this blog post, we discuss how to address the problem of limited human effort by enabling machines to “learn from human explanations.”
We hear about GANs a lot, but what are they, why should you care, and how do you get started with them?
Neo4j webinar — November 18, 2021, 16:00 BT, 17:00 CET
Maybe you’ve heard about using graph data, or relationships, in machine learning pipelines for better accuracy or new types of predictions. But you’ve probably wondered: how exactly do I improve my predictive accuracy? The answer is graph embeddings: a technique to translate your graph into the right representation of your problem. We’ll provide a conceptual overview and a hands-on demo of generating embeddings from a real-world, consumer dataset, and using them to make accurate recommendations.
Covering universities, large tech companies, and more, here are some AI research labs pushing the field to the next level.
Many organizations hope that by the time an opportunity arises, they’ll have a plan in place to handle both the risk and opportunity of monetizing any new market by using data science for risk management.
Featuring leaders from Stanford, Intel Labs, UC Irvine, and more, here are the ODSC West 2021 Keynotes that you can learn from this November.
Attend the ODSC West AI Expo & Demo Hall for free and hear from companies like Microsoft, HP, Oracle, Intel, and more.
Get your ODSC West Platinum Pass today to spend 3 days taking a deep dive into NLP, Deep Learning, MLOps and more from some of the best and brightest minds in data science and AI.
Ai+ Highlight of the Week: Unsupervised Learning 3 — Deep Unsupervised Learning, Semi-Supervised Learning, and Generative Models
- Ankur Patel | Head of Data | Glean
Check out the first 20 minutes of on-demand training to learn how to build unsupervised, supervised, and semi-supervised (using autoencoders) credit card fraud detection systems.