Python

Python News Roundup: September 2024

As the autumn leaves start to fall, signaling the transition to cooler weather, the Python community has warmed up to a series of noteworthy developments. Last month, a new maintenance release of Python 3.12.5 was introduced, reinforcing the language’s ongoing commitment to stability and security. On a parallel note, Python continues its reign as the top programming language according to IEEE Spectrum’s annual rankings. This sentiment is echoed by the Python Developers Survey 2023 results, which reveal intriguing trends and […]

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Artificial intelligence Leave a comment

GraphRAG auto-tuning provides rapid adaptation to new domains

GraphRAG uses large language models (LLMs) to create a comprehensive knowledge graph that details entities and their relationships from any collection of text documents. This graph enables GraphRAG to leverage the semantic structure of the data and generate responses to complex queries that require a broad understanding of the entire text. In previous blog posts, we introduced GraphRAG and demonstrated how it could be applied to news articles. In this blog post, we show that it can also  

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Machine Learning

5 Emerging AI Technologies That Will Shape the Future of Machine Learning

5 Emerging AI Technologies That Will Shape the Future of Machine LearningImage by Editor | Midjourney Artificial intelligence is not just altering the way we interact with technology; it’s reshaping the very foundations of machine learning. As we stand on the brink of innovative breakthroughs, understanding emerging AI technologies becomes essential to grasp their profound implications on future applications and industries. This exploration is not merely academic—it’s a guide to influencing and capitalizing on the next wave of technological revolution. […]

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Machine Learning

Detecting and Overcoming Perfect Multicollinearity in Large Datasets

One of the significant challenges statisticians and data scientists face is multicollinearity, particularly its most severe form, perfect multicollinearity. This issue often lurks undetected in large datasets with many features, potentially disguising itself and skewing the results of statistical models. In this post, we explore the methods for detecting, addressing, and refining models affected by perfect multicollinearity. Through practical analysis and examples, we aim to equip you with the tools necessary to enhance your models’ robustness and interpretability, ensuring that […]

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Python

Quiz: Lists vs Tuples in Python

Interactive Quiz ⋅ 10 QuestionsBy Leodanis Pozo Ramos Share Challenge yourself with this quiz to evaluate and deepen your understanding of Python lists and tuples. You’ll explore key concepts, such as how to create and manipulate these data types, while also learning best practices for using them efficiently in your code. You can take this quiz after reading the Lists vs Tuples in Python tutorial. The quiz contains 10 questions and there is no time limit. You’ll get 1 point […]

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Machine Learning

Interior Design with Stable Diffusion (8-day mini-course)

At its core, Stable Diffusion is a deep learning model that can generate pictures. Together with some other models and UI, you can consider that as a tool to help you create pictures in a new dimension that not only you can provide instructions on how the picture looks like, but also the generative model to brainstorm what you didn’t specify. In this 7-part crash course, you will learn from examples how to make use of Stable Diffusion to finish […]

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Machine Learning

10 Machine Learning Algorithms Explained Using Real-World Analogies

10 Machine Learning Algorithms Explained Using Real-World Analogies When I was in high school and studied complex mathematics problems, I always used to think about why we were studying them or why they were useful. I was unable to understand and find their usage in the real world. Since machine learning is also a trending topic that many people want to explore, the complex mathematics and abstraction behind machine learning algorithms make it difficult for beginners to appreciate and learn […]

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Machine Learning

The Power of Pipelines

Machine learning projects often require the execution of a sequence of data preprocessing steps followed by a learning algorithm. Managing these steps individually can be cumbersome and error-prone. This is where sklearn pipelines come into play. This post will explore how pipelines automate critical aspects of machine learning workflows, such as data preprocessing, feature engineering, and the incorporation of machine learning algorithms. Let’s get started. The Power of PipelinesPhoto by Quinten de Graaf. Some rights reserved. Overview This post is […]

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Machine Learning

Tips for Effective Feature Selection in Machine Learning

Tips for Effective Feature Selection in Machine LearningImage by Author | Created on Canva When training a machine learning model, you may sometimes work with datasets with a large number of features. However, only a small subset of these features will actually be important for the model to make predictions. Which is why you need feature selection to identify these helpful features. This article covers useful tips for feature selection. We’ll not look at feature selection techniques in depth. But […]

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Systems and networking Leave a comment

Collaborators: Silica in space with Richard Black and Dexter Greene

[TEASER ENDS]  GRETCHEN HUIZINGA: You’re listening to Collaborators, a Microsoft Research Podcast showcasing the range of expertise that goes into transforming mind-blowing ideas into world-changing technologies. I’m Dr. Gretchen Huizinga. [MUSIC FADES]  Today I’m talking to Dr. Richard Black, a senior principal research manager and the research director of Project Silica at Microsoft Research. And with him is Dexter Greene, a rising freshman at the University of Michigan and a recent graduate of Avenues: The World School in New York […]

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