Author: Deep Learner

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Accounting for past imaging studies: Enhancing radiology AI and reporting

The use of self-supervision from image-text pairs has been a key enabler in the development of scalable and flexible vision-language AI models in not only general domains but also in biomedical domains such as radiology. The goal in the radiology setting is to produce rich training signals without requiring manual labels so the models can learn to accurately recognize and locate findings in the images and relate them to content in radiology reports. Radiologists use radiology reports to describe imaging […]

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Python

Python Basics: Reading and Writing Files

Files are everywhere in the modern world. They’re the medium in which data is digitally stored and transferred. Chances are, you’ve opened dozens, if not hundreds, of files just today! Now it’s time to read and write files with Python. In this video course, you’ll learn how to: Understand the difference between text and binary files Learn about character encodings and line endings Work with file objects in Python Read and write character data in various file modes Use open(), […]

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Python

Python News: What’s New From May 2023

May 2023 was an important month for Python, as the upcoming Python 3.12 version is now feature complete. You can dig into a lot of information about Python and its development by reading the coverage of the Language Summit and watching videos from PyCon US. Modular has announced a new programming language that’s based on Python. Grab a cup of your favorite beverage and sit down with the most important Python news from the last month. Python 3.12 in Beta […]

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Python

Understanding CPUs can help speed up Numba and NumPy code

When you need to speed up your NumPy processing—or just reduce your memory usage—the Numba just-in-time compiler is a great tool. It lets you write Python code that gets compiled at runtime to machine code, allowing you to get the kind of speed improvements you’d get from languages like C, Fortran, or Rust. Or at least, that’s the theory. In practice, your initial Numba code may be no faster than the NumPy equivalent. But you can do better, once you […]

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Neural Machine Translation (NMT), NMT Leave a comment

Highlights from Machine Translation and Multilinguality in May 2023

Here are a few papers I found most interesting in the flood of new pre-prints on arXiv. There was ACL’s camera-ready deadline and the start of the EMNLP anonymity period, so there were many more papers than usual. What is the best recipe for character-level encoder-only modeling? A paper from DeepMind accepted to ACL 2023 systematically (and empirically) studies how to train a BERT-like model that works directly with character-level inputs using existing architectural building blocks. Transformers work well with […]

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AI Frontiers: The future of causal reasoning with Emre Kiciman and Amit Sharma

[MUSIC FADES] Emre, Amit, let’s jump right in. I’m so excited to speak with you both about causal reasoning. And this is such a timely conversation because we’re living through the rise of generative pretrained models, specifically large language models. And when I’ve engaged with GPT-4 in dialogue, depending on what I ask, it can appear to be doing something resembling causal reasoning. And as a machine learning person myself, I have to say this is not something that I’d expected […]

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Python

What’s the Zen of Python?

If you’ve been learning Python long enough, then you’ve likely seen or heard about the Zen of Python. Experienced Pythonistas often refer to it as a source of wisdom and guidance, especially when they want to settle an argument about certain design decisions in a piece of code. Others take these principles even more seriously by considering them a sort of Pythonic decalogue. In this tutorial, you’ll learn where to find the Zen of Python, how it came into existence, […]

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