From ff65b5192fc146acffb06001fb3e4755cc95ea49 Mon Sep 17 00:00:00 2001 From: Krishna Dave Date: Thu, 30 Oct 2025 09:13:59 +0530 Subject: [PATCH 1/3] Added link to github discussions in the latest minutes --- website/_posts/2025-10-24-Meeting-Minutes.md | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/website/_posts/2025-10-24-Meeting-Minutes.md b/website/_posts/2025-10-24-Meeting-Minutes.md index 0daa17cb91..e84975ef0f 100644 --- a/website/_posts/2025-10-24-Meeting-Minutes.md +++ b/website/_posts/2025-10-24-Meeting-Minutes.md @@ -19,4 +19,5 @@ category: minutes ### Next Steps * Krishna, Wes to learn more about PyPi and make accounts * New release 0.4.1 to be done, currently on 0.4. -* Andrew to try using ATR for 0.4.1 release \ No newline at end of file +* Andrew to try using ATR for 0.4.1 release +[Minutes](https://github.com/apache/mahout/discussions/551) on GitHub Discussions. \ No newline at end of file From 63f9a8bf1d1a6f0d94739cd9b450a632eaa24733 Mon Sep 17 00:00:00 2001 From: Krishna Dave Date: Thu, 30 Oct 2025 09:42:17 +0530 Subject: [PATCH 2/3] Updated papers.md --- website/papers.md | 40 ++++++++++++++++++++++++++++++++++++---- 1 file changed, 36 insertions(+), 4 deletions(-) diff --git a/website/papers.md b/website/papers.md index 6b0d2f914a..3771ea099b 100644 --- a/website/papers.md +++ b/website/papers.md @@ -3,8 +3,40 @@ layout: page title: Papers --- -# Papers +## Overview -{% for paper in site.papers %} -- [{{ paper.title }}]({{ paper.url }}) -{% endfor %} +Apache Mahout is an open-source framework designed for creating scalable machine learning algorithms and distributed linear algebra operations. Originally built on top of Hadoop’s MapReduce framework, Mahout has evolved into a mathematically expressive environment for building high-performance machine learning systems. + +Today, Mahout leverages distributed computing engines such as **Apache Spark**, **Apache Flink**, and **H2O** through its **Samsara DSL** — a powerful domain-specific language for matrix and vector mathematics. This shift allows Mahout to support large-scale data processing and advanced analytical workloads while maintaining concise mathematical syntax. + +## Purpose of This Page + +This section curates research papers, academic studies, and technical references that align with Mahout’s objectives — from **distributed linear algebra** and **matrix factorization** to **recommendation systems**, **clustering**, and **scalable machine learning algorithms**. + +Each paper summarized here provides theoretical or practical insights into the technologies that influence Mahout’s ongoing development and implementation. + +## Topics Covered + +The listed works and references generally relate to: + +- **Distributed Linear Algebra and Matrix Computations** + Techniques that power Mahout’s core algebra engine for scalable data processing. + +- **Recommender Systems and Collaborative Filtering** + Foundational research behind Mahout’s recommendation algorithms. + +- **Clustering and Classification Methods** + Studies on scalable implementations of k-Means, Naive Bayes, and other algorithms. + +- **Scalable Machine Learning Frameworks** + Research on distributed computing paradigms that inspired Mahout’s move from MapReduce to Samsara. + +## Featured Reference + +* [Apache Mahout: Scalable Machine Learning and Distributed Linear Algebra](papers/apache-mahout-scalable-machine-learning) + +This reference summarizes Mahout’s evolution and its significance in bridging the gap between mathematical theory and real-world distributed machine learning applications. + +--- + +Contributors are encouraged to expand this section by adding summaries of relevant research papers in the `/website/_papers/` directory following the existing template. From 0562c9857e2036dbd95d5550b9f050bf977eeda3 Mon Sep 17 00:00:00 2001 From: Krishna Dave Date: Thu, 30 Oct 2025 21:43:56 +0530 Subject: [PATCH 3/3] Revert changes to website/papers.md --- website/papers.md | 40 ++++------------------------------------ 1 file changed, 4 insertions(+), 36 deletions(-) diff --git a/website/papers.md b/website/papers.md index 3771ea099b..6b0d2f914a 100644 --- a/website/papers.md +++ b/website/papers.md @@ -3,40 +3,8 @@ layout: page title: Papers --- -## Overview +# Papers -Apache Mahout is an open-source framework designed for creating scalable machine learning algorithms and distributed linear algebra operations. Originally built on top of Hadoop’s MapReduce framework, Mahout has evolved into a mathematically expressive environment for building high-performance machine learning systems. - -Today, Mahout leverages distributed computing engines such as **Apache Spark**, **Apache Flink**, and **H2O** through its **Samsara DSL** — a powerful domain-specific language for matrix and vector mathematics. This shift allows Mahout to support large-scale data processing and advanced analytical workloads while maintaining concise mathematical syntax. - -## Purpose of This Page - -This section curates research papers, academic studies, and technical references that align with Mahout’s objectives — from **distributed linear algebra** and **matrix factorization** to **recommendation systems**, **clustering**, and **scalable machine learning algorithms**. - -Each paper summarized here provides theoretical or practical insights into the technologies that influence Mahout’s ongoing development and implementation. - -## Topics Covered - -The listed works and references generally relate to: - -- **Distributed Linear Algebra and Matrix Computations** - Techniques that power Mahout’s core algebra engine for scalable data processing. - -- **Recommender Systems and Collaborative Filtering** - Foundational research behind Mahout’s recommendation algorithms. - -- **Clustering and Classification Methods** - Studies on scalable implementations of k-Means, Naive Bayes, and other algorithms. - -- **Scalable Machine Learning Frameworks** - Research on distributed computing paradigms that inspired Mahout’s move from MapReduce to Samsara. - -## Featured Reference - -* [Apache Mahout: Scalable Machine Learning and Distributed Linear Algebra](papers/apache-mahout-scalable-machine-learning) - -This reference summarizes Mahout’s evolution and its significance in bridging the gap between mathematical theory and real-world distributed machine learning applications. - ---- - -Contributors are encouraged to expand this section by adding summaries of relevant research papers in the `/website/_papers/` directory following the existing template. +{% for paper in site.papers %} +- [{{ paper.title }}]({{ paper.url }}) +{% endfor %}