Explores four main approaches to building and enhancing reasoning capabilities in Large Language Models (LLMs) for complex tasks.
A guide to the best newsletters, blogs, and resources for staying updated on the fast-moving field of Artificial Intelligence in 2025.
A summary and discussion of Chapter 1 of Chip Huyen's book, exploring the definition of AI Engineering, its distinction from ML, and the AI Engineering stack.
Interview with Dr. Nick Feamster on network measurement, machine learning, and the Internet Equity Initiative's work on broadband access.
A researcher reflects on 2024 highlights in AI, covering societal impacts, software tools like Scikit-learn, and technical research on tabular data and language models.
An overview of Microsoft Azure's suite of AI services, including prebuilt APIs, machine learning, and cognitive tools for building intelligent applications.
A curated list of notable LLM and AI research papers published in 2024, providing a resource for those interested in the latest developments.
Introduces Label-Studio, an open-source tool for annotating text, image, audio, and video data for AI/ML projects, highlighting its ease of use and features.
A guide on transitioning into AI careers, distinguishing between working 'on' AI models and 'in' AI infrastructure, products, and engineering processes.
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Announces 7 new free R programming books added to the Big Book of R collection, covering topics like machine learning, data science, and software engineering.
A guide on starting and running a weekly paper club for learning about AI/ML research papers and building a technical community.
Author shares detailed experience and study tips for passing both AWS Machine Learning Engineer Associate and Machine Learning Specialty certification exams.
Key lessons from 2024 ML conferences on building effective machine learning systems, covering reward functions, trade-offs, and practical engineering advice.
Podcast interview with Gorkem Ercan discussing Eclipse Foundation, AI/ML adoption in enterprises, CI/CD practices, and open source development.
Explores whether large language models like ChatGPT truly reason or merely recite memorized text from their training data, examining their logical capabilities.
Exploration of Microsoft's 1.4 billion global building footprint dataset, created via ML on satellite imagery, including setup and analysis steps.
A developer shares their experience taking the AWS Certified AI Practitioner beta exam, covering study methods, key topics, and exam structure.
A comprehensive guide to building interactive data applications using the Streamlit framework, covering setup, visualization, ML integration, and deployment.
An animated exploration of UMAP, a state-of-the-art dimensionality reduction algorithm, applied to the classic MNIST dataset of handwritten digits.
A technical blog post documenting notes and code examples while studying machine learning concepts from 'The Little Learner' textbook.
