Quiz: Python Protocols: Leveraging Structural Subtyping

Interactive Quiz ⋅ 11 QuestionsBy Leodanis Pozo Ramos Share Or copy the link: Copied! Happy Pythoning! Test your understanding of how to create and use Python protocols while providing type hints for your functions, variables, classes, and methods. Take this quiz after reading our Python Protocols: Leveraging Structural Subtyping tutorial. The quiz contains 11 questions and there is no time limit. You’ll get 1 point for each correct answer. At    

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Quiz: Logging in Python

Interactive Quiz ⋅ 9 QuestionsBy Philipp Acsany Share Or copy the link: Copied! Happy Pythoning! In this quiz, you’ll test your understanding of Python’s logging module. Logging is a very useful tool in a programmer’s toolbox. It can help you develop a better understanding of the flow of a program and discover scenarios that you might not have thought of while developing. Logs provide developers with an extra set of eyes that are constantly looking    

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Quiz: Hugging Face Transformers

Interactive Quiz ⋅ 6 QuestionsBy Bartosz Zaczyński Share Or copy the link: Copied! Happy Pythoning! In this quiz, you’ll test your understanding of Hugging Face Transformers. This library is a popular choice for working with transformer models in natural language processing tasks, computer vision, and other machine learning applications. The quiz contains 6 questions and there is no time limit. You’ll get 1 point for each correct answer. At the    

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Hugging Face Transformers: Leverage Open-Source AI in Python

Transformers is a powerful Python library created by Hugging Face that allows you to download, manipulate, and run thousands of pretrained, open-source AI models. These models cover multiple tasks across modalities like natural language processing, computer vision, audio, and multimodal learning. Using pretrained open-source models can reduce costs, save the time needed to train models from scratch, and give you more control over the models you deploy. Throughout this tutorial, you’ll gain a conceptual understanding of Hugging Face’s AI offerings and learn how to […]

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Lessons learned from analyzing values in multilingual encoders and what it means for LLMs

This post is a hindsight on two studies on multilingual sentence embeddings we published a year ago and comments on what I think people analyzing LLMs today should take away from them. In late 2022, we (which mainly was the work of Kathy Hämmerl from Munich and Björn Diesenroth and Patrick Schramowski from Darmstadt) finished a paper called Speaking Multiple Languages Affects the Moral Bias of Language Models (later published in Findings of ACL 2023) where we tried to compare […]

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pandas GroupBy: Grouping Real World Data in Python

Whether you’ve just started working with pandas and want to master one of its core capabilities, or you’re looking to fill in some gaps in your understanding about .groupby(), this course will help you to break down and visualize a pandas GroupBy operation from start to finish. This course is meant to complement the official pandas documentation and the pandas Cookbook, where there are self-contained, bite-sized examples. Here, however, you’ll focus on three more involved walkthroughs that use real-world datasets. […]

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Understanding LangChain LLM Output Parser

The large Language Model, or LLM, has revolutionized how people work. By helping users generate the answer from a text prompt, LLM can do many things, such as answering questions, summarizing, planning events, and more. However, there are times when the output from LLM is not up to our standard. For example, the text generated could be thoroughly wrong and need further direction. This is where the LLM Output Parser could help. By standardizing the output result with LangChain Output […]

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Microsoft at ICML 2024: Innovations in machine learning

In an era increasingly steered by data, machine learning is a pivotal force, transforming vast amounts of information into actionable intelligence with unprecedented speed and accuracy. For example, recent advances in machine learning have led to breakthroughs in precision health, helping doctors make more informed decisions about patient care. Similarly, in climate science, machine learning is improving scientists’ ability to predict and mitigate the impact of extreme weather events. These innovations illustrate that machine learning not only streamlines workflows, it […]

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Using Machine Learning in Customer Segmentation

Image by Editor | Midjourney In the past, businesses grouped customers based on simple things like age or gender. Now, machine learning has changed this process. Machine learning algorithms can analyze large amounts of data. In this article, we will explore how machine learning improves customer segmentation. Introduction to Customer Segmentation Customer segmentation divides customers into different groups. These groups are based on similar traits or behaviors. The main goal is to understand each group better. This helps businesses create […]

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Quiz: Python Strings and Character Data

Interactive Quiz ⋅ 11 QuestionsBy Leodanis Pozo Ramos Share Or copy the link: Copied! Happy Pythoning! This quiz will evaluate your understanding of Python’s string data type and test your knowledge about manipulating textual data with string objects. You’ll cover the basics of creating strings using literals and the str() function, applying string methods, using operators and built-in functions with strings, indexing and slicing strings, and more! Take this quiz after reading our Strings and    

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