Abstracts: September 30, 2024

MARTIN GRAYSON: Pleasure, thank you.  DANIELA MASSICETI: Thanks very much, Amber. Nice to be here.  TINGLE: So, Daniela, let’s start with a Find My Things overview. What is it, how does it work, and who’s it for?  MASSICETI: I think the best way I can describe Find My Things is a personalizable object recognizer. So when we think about object recognizers in the past, they’ve, kind of, been what I would call generic object recognizers. So they can only really […]

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Navigating Missing Data Challenges with XGBoost

XGBoost has gained widespread recognition for its impressive performance in numerous Kaggle competitions, making it a favored choice for tackling complex machine learning challenges. Known for its efficiency in handling large datasets, this powerful algorithm stands out for its practicality and effectiveness. In this post, we will apply XGBoost to the Ames Housing dataset to demonstrate its unique capabilities. Building on our prior discussion of the Gradient Boosting Regressor (GBR), we will explore key features that differentiate XGBoost from GBR, […]

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Quiz: Python 3.13: Free Threading and a JIT Compiler

Interactive Quiz ⋅ 16 QuestionsBy Bartosz Zaczyński Share In this quiz, you’ll test your understanding of the new features in Python 3.13. By working through this quiz, you’ll revisit how to compile a custom Python build, disable the Global Interpreter Lock (GIL), enable the Just-In-Time (JIT) compiler, determine the availability of new features at runtime, assess the performance improvements in Python 3.13, and make a C extension module targeting Python’s new ABI. The quiz contains 16 questions and there is […]

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Quiz: Python 3.13: Cool New Features for You to Try

Interactive Quiz ⋅ 9 QuestionsBy Geir Arne Hjelle Share In this quiz, you’ll test your understanding of Python 3.13: Cool New Features for You to Try. By working through this quiz, you’ll review the key updates and improvements in this version of Python. The quiz contains 9 questions and there is no time limit. You’ll get 1 point for each correct answer. At the end of the quiz, you’ll receive a total score. The maximum score is 100%. Good luck! […]

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Quiz: Syntactic Sugar: Why Python Is Sweet and Pythonic

Interactive Quiz ⋅ 10 QuestionsBy Leodanis Pozo Ramos Share Test your understanding of Python’s most common pieces of syntactic sugar and how they make your code more Pythonic and readable. Take this quiz after reading our Syntactic Sugar: Why Python is Sweet and Pythonic tutorial. The quiz contains 10 questions and there is no time limit. You’ll get 1 point for each correct answer. At the end of the quiz, you’ll receive a total score. The maximum score is 100%. […]

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Boosting Over Bagging: Enhancing Predictive Accuracy with Gradient Boosting Regressors

Ensemble learning techniques primarily fall into two categories: bagging and boosting. Bagging improves stability and accuracy by aggregating independent predictions, whereas boosting sequentially corrects the errors of prior models, improving their performance with each iteration. This post begins our deep dive into boosting, starting with the Gradient Boosting Regressor. Through its application on the Ames Housing Dataset, we will demonstrate how boosting uniquely enhances models, setting the stage for exploring various boosting techniques in upcoming posts. Let’s get started. Boosting […]

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Building 3 Fun AI Applications with ControlFlow

Building 3 Fun AI Applications with ControlFlowImage by Author | Canva Pro The AI industry is rapidly advancing towards creating solutions using large language models (LLMs) and maximizing the potential of AI models. Companies are seeking tools that seamlessly integrate AI into existing codebases without the hefty costs associated with hiring professionals and acquiring resources. This is where Controlflow comes into play. With ControlFlow, you can develop complex AI applications using just a few lines of code. In this tutorial, […]

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Microsoft Research Forum Episode 4: The future of multimodal models, a new “small” language model, and other AI updates

Microsoft Research Forum is a continuous exchange of ideas about science and technology research in the era of general AI. In the latest episode (opens in new tab), researchers discussed the latest multimodal AI models, advanced benchmarks for AI evaluation and model self-improvement, and an entirely new kind of computer for AI inference and hard optimization. Researchers at Microsoft are working to explore breakthrough technology that can help advance everything from weather prediction to materials design.  Below is a brief recap […]

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Python 3.13 Preview: A Modern REPL

One of Python’s strong points is its interactive capabilities. By running python you start the interactive interpreter, or REPL, which allows you to perform quick calculations or explore and experiment with your code. In Python 3.13, the interactive interpreter has been completely redesigned with new modern features. Python’s REPL has remained largely unchanged for decades. Instead, alternative interpreters like IPython, bpython, and ptpython have addressed some of the built-in REPL’s shortcomings, providing more convenient interactive workflows for developers. As you’re […]

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Research Focus: Week of September 23, 2024

Welcome to Research Focus, a series of blog posts that highlights notable publications, events, code/datasets, new hires and other milestones from across the research community at Microsoft. NEW RESEARCH ProbTS: Benchmarking Point and Distributional Forecasting across Diverse Prediction Horizons Time-series forecasting is a technique used to predict future values based on previously observed data points over time. It has extensive applications for traffic flow, renewable energy, retail, finance, and climate, among other uses. For these applications,  

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