<?xml version="1.0" encoding="UTF-8"?>
<rss version="2.0">
  <channel>
    <title>PyPI recent updates for dynamicml</title>
    <link>https://pypi.org/project/dynamicml/</link>
    <description>Recent updates to the Python Package Index for dynamicml</description>
    <language>en</language>    <item>
      <title>1.1.5</title>
      <link>https://pypi.org/project/dynamicml/1.1.5/</link>
      <description>A lightweight binary image classification system built with scikit‑learn, focusing on k‑Nearest Neighbors (kNN) and classical ML models. It features dynamic, model‑aware image preprocessing (HOG, scaling, PCA) that adapts automatically to image characteristics, enabling efficient training and reliable inference for custom datasets.</description>
<author>ganiisunkara@gmail.com, sanmukasaikudirella@gmail.com, mouryakarrothu@gmail.com, sunayananeti12@gmail.com, kirankumartech18@gmail.com</author>      <pubDate>Thu, 26 Mar 2026 17:17:45 GMT</pubDate>
    </item>    <item>
      <title>1.1.4</title>
      <link>https://pypi.org/project/dynamicml/1.1.4/</link>
      <description>A lightweight binary image classification system built with scikit‑learn, focusing on k‑Nearest Neighbors (kNN) and classical ML models. It features dynamic, model‑aware image preprocessing (HOG, scaling, PCA) that adapts automatically to image characteristics, enabling efficient training and reliable inference for custom datasets.</description>
<author>ganiisunkara@gmail.com, sanmukasaikudirella@gmail.com, mouryakarrothu@gmail.com, sunayananeti12@gmail.com, kirankumartech18@gmail.com</author>      <pubDate>Thu, 26 Mar 2026 16:30:13 GMT</pubDate>
    </item>    <item>
      <title>1.1.3</title>
      <link>https://pypi.org/project/dynamicml/1.1.3/</link>
      <description>A lightweight binary image classification system built with scikit‑learn, focusing on k‑Nearest Neighbors (kNN) and classical ML models. It features dynamic, model‑aware image preprocessing (HOG, scaling, PCA) that adapts automatically to image characteristics, enabling efficient training and reliable inference for custom datasets.</description>
<author>ganiisunkara@gmail.com, sanmukasaikudirella@gmail.com, mouryakarrothu@gmail.com, sunayananeti12@gmail.com, kirankumartech18@gmail.com</author>      <pubDate>Thu, 26 Mar 2026 16:13:43 GMT</pubDate>
    </item>    <item>
      <title>1.1.2</title>
      <link>https://pypi.org/project/dynamicml/1.1.2/</link>
      <description>A lightweight binary image classification system built with scikit‑learn, focusing on k‑Nearest Neighbors (kNN) and classical ML models. It features dynamic, model‑aware image preprocessing (HOG, scaling, PCA) that adapts automatically to image characteristics, enabling efficient training and reliable inference for custom datasets.</description>
<author>ganiisunkara@gmail.com, sanmukasaikudirella@gmail.com, mouryakarrothu@gmail.com, sunayananeti12@gmail.com, kirankumartech18@gmail.com</author>      <pubDate>Tue, 10 Mar 2026 15:49:51 GMT</pubDate>
    </item>    <item>
      <title>1.1.1</title>
      <link>https://pypi.org/project/dynamicml/1.1.1/</link>
      <description>A lightweight binary image classification system built with scikit‑learn, focusing on k‑Nearest Neighbors (kNN) and classical ML models. It features dynamic, model‑aware image preprocessing (HOG, scaling, PCA) that adapts automatically to image characteristics, enabling efficient training and reliable inference for custom datasets.</description>
<author>ganiisunkara@gmail.com, sanmukasaikudirella@gmail.com, mouryakarrothu@gmail.com, sunayananeti12@gmail.com, kirankumartech18@gmail.com</author>      <pubDate>Fri, 06 Mar 2026 16:23:39 GMT</pubDate>
    </item>    <item>
      <title>1.1.0</title>
      <link>https://pypi.org/project/dynamicml/1.1.0/</link>
      <description>A lightweight binary image classification system built with scikit‑learn, focusing on k‑Nearest Neighbors (kNN) and classical ML models. It features dynamic, model‑aware image preprocessing (HOG, scaling, PCA) that adapts automatically to image characteristics, enabling efficient training and reliable inference for custom datasets.</description>
<author>ganiisunkara@gmail.com, sanmukasaikudirella@gmail.com, mouryakarrothu@gmail.com, kirankumartech18@gmail.com</author>      <pubDate>Mon, 02 Mar 2026 15:05:14 GMT</pubDate>
    </item>    <item>
      <title>1.0.2</title>
      <link>https://pypi.org/project/dynamicml/1.0.2/</link>
      <description>A lightweight binary image classification system built with scikit‑learn, focusing on k‑Nearest Neighbors (kNN) and classical ML models. It features dynamic, model‑aware image preprocessing (HOG, scaling, PCA) that adapts automatically to image characteristics, enabling efficient training and reliable inference for custom datasets.</description>
<author>ganiisunkara@gmail.com, sanmukasaikudirella@gmail.com, mouryakarrothu@gmail.com, kirankumartech18@gmail.com</author>      <pubDate>Mon, 02 Mar 2026 10:12:14 GMT</pubDate>
    </item>    <item>
      <title>1.0.1</title>
      <link>https://pypi.org/project/dynamicml/1.0.1/</link>
      <description>A lightweight binary image classification system built with scikit‑learn, focusing on k‑Nearest Neighbors (kNN) and classical ML models. It features dynamic, model‑aware image preprocessing (HOG, scaling, PCA) that adapts automatically to image characteristics, enabling efficient training and reliable inference for custom datasets.</description>
<author>ganiisunkara@gmail.com, sanmukasaikudirella@gmail.com, mouryakarrothu@gmail.com, kirankumartech18@gmail.com</author>      <pubDate>Sun, 01 Mar 2026 18:09:01 GMT</pubDate>
    </item>    <item>
      <title>1.0.0</title>
      <link>https://pypi.org/project/dynamicml/1.0.0/</link>
      <description>A lightweight binary image classification system built with scikit‑learn, focusing on k‑Nearest Neighbors (kNN) and classical ML models. It features dynamic, model‑aware image preprocessing (HOG, scaling, PCA) that adapts automatically to image characteristics, enabling efficient training and reliable inference for custom datasets.</description>
<author>ganiisunkara@gmail.com, sanmukasaikudirella@gmail.com, mouryakarrothu@gmail.com</author>      <pubDate>Sun, 01 Mar 2026 17:10:00 GMT</pubDate>
    </item>  </channel>
</rss>