Data Science Dojo

DECEMBER 8, 2023

Zero-shot, one-shot, and few-shot learning are redefining how machines adapt and learn, promising a future where adaptability and generalization reach unprecedented levels. Source: Photo by Hal Gatewood on Unsplash In this exploration, we navigate from the basics of supervised learning to the forefront of adaptive models.

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Data Science Dojo

DECEMBER 8, 2023

Zero-shot, one-shot, and few-shot learning are redefining how machines adapt and learn, promising a future where adaptability and generalization reach unprecedented levels. Source: Photo by Hal Gatewood on Unsplash In this exploration, we navigate from the basics of supervised learning to the forefront of adaptive models.

Supervised Learning 195

Supervised Learning Machine Learning Machine Learning Artificial Intelligence 195

Dataconomy

APRIL 18, 2023

Additionally, it is crucial to comprehend the fundamental concepts that underlie AI, including neural networks, algorithms, and data structures. AI systems use a combination of algorithms, machine learning techniques, and data analytics to simulate human intelligence. What is artificial intelligence?

Artificial Intelligence 113

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BAIR

APRIL 6, 2023

This approach is known as “Fleet Learning,” a term popularized by Elon Musk in 2016 press releases about Tesla Autopilot and used in press communications by Toyota Research Institute , Wayve AI , and others. Using this formalism, we can now instantiate and compare IFL algorithms (i.e., allocation policies) in a principled way.

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How to Learn Machine Learning

OCTOBER 10, 2024

The quality of your training data in Machine Learning (ML) can make or break your entire project. This article explores real-world cases where poor-quality data led to model failures, and what we can learn from these experiences. Machine learning algorithms rely heavily on the data they are trained on. The lesson here?

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Machine Learning Machine Learning Data Quality Algorithm 52

Snorkel AI

MARCH 1, 2023

Foundation models are large AI models trained on enormous quantities of unlabeled data—usually through self-supervised learning. What is self-supervised learning? Self-supervised learning is a kind of machine learning that creates labels directly from the input data. Find out in the guide below.

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Snorkel AI

FEBRUARY 17, 2023

I share this because it shows where things were in 2016; it was exciting to find one label error. At the time, back in 2016, the MNIST dataset had been cited 30,000 times. In the beginning, we looked at the binary classification problem of how do you find label errors in data and how do you learn?

Machine Learning 52

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