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                	<title>Fine-Tuning Explained for Noobs (How Pretrained Models Learn New Skills)</title>
               		<description><![CDATA[You don't need a PhD to understand fine-tuning. This article explains how pretrained models learn new skills through fine-tuning.]]></description>
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                	<pubDate>Fri, 10 Jul 2026 14:00:32 +0000</pubDate>
                	<dc:creator><![CDATA[Kanwal Mehreen]]></dc:creator>
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                	<title>Local Video Summarization Pipeline: Processing Frames with SmolVLM2-2.2B</title>
               		<description><![CDATA[SmolVLM2-2.2B sits at a genuinely useful point on the capability-size trade-off curve; small enough to run on a single consumer GPU, capable enough to produce video summaries that are actually useful for real workflows.]]></description>
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                	<pubDate>Fri, 10 Jul 2026 12:00:51 +0000</pubDate>
                	<dc:creator><![CDATA[Shittu Olumide]]></dc:creator>
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                	<title>Running OpenClaw with Ollama</title>
               		<description><![CDATA[This article covers the full path from zero to a running private research assistant on Telegram, including configuring the context length correctly, connecting the channel, enabling web search, and deploying it headlessly in Docker.]]></description>
                	<link>https://www.kdnuggets.com/running-openclaw-with-ollama</link>
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                	<pubDate>Thu, 09 Jul 2026 14:00:15 +0000</pubDate>
                	<dc:creator><![CDATA[Shittu Olumide]]></dc:creator>
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                	<title>7 Steps to Automating Descriptive Statistics with Python</title>
               		<description><![CDATA[Stop writing <code>mean()</code> and <code>std()</code> for every column. Learn how to automate descriptive statistics in Python and generate publication-ready summary tables in just a few steps.]]></description>
                	<link>https://www.kdnuggets.com/7-steps-to-automating-descriptive-statistics-with-python</link>
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                	<pubDate>Thu, 09 Jul 2026 12:00:39 +0000</pubDate>
                	<dc:creator><![CDATA[Kanwal Mehreen]]></dc:creator>
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                	<title>How to Clean Messy CSV Files with Python: A Beginner’s Guide</title>
               		<description><![CDATA[Learn how to clean CSV files with pandas by handling missing values, duplicate rows, messy text, wrong data types, mixed date formats, invalid emails, and currency values.]]></description>
                	<link>https://www.kdnuggets.com/how-to-clean-messy-csv-files-with-python-a-beginners-guide</link>
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                	<pubDate>Wed, 08 Jul 2026 15:10:39 +0000</pubDate>
                	<dc:creator><![CDATA[Abid Ali Awan]]></dc:creator>
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                	<title>SQL vs Pandas vs AI Agents: Which Solves Analytics Problems Best?</title>
               		<description><![CDATA[Same three analytics problems, three tools, eight dimensions,  measured with real execution times and real agent prompts.]]></description>
                	<link>https://www.kdnuggets.com/sql-vs-pandas-vs-ai-agents-which-solves-analytics-problems-best</link>
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                	<pubDate>Tue, 07 Jul 2026 16:00:29 +0000</pubDate>
                	<dc:creator><![CDATA[Nate Rosidi]]></dc:creator>
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                	<title>Zero-Shot Local Document Parsing with Gemma 4: Treating PDFs as Images</title>
               		<description><![CDATA[Treating PDFs as images and feeding those images to Gemma 4 dissolves the scanned-versus-digital distinction that makes every text-extraction pipeline fragile. Fix that.]]></description>
                	<link>https://www.kdnuggets.com/zero-shot-local-document-parsing-with-gemma-4-treating-pdfs-as-images</link>
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                	<pubDate>Tue, 07 Jul 2026 14:00:04 +0000</pubDate>
                	<dc:creator><![CDATA[Shittu Olumide]]></dc:creator>
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                	<title>10 Probability Concepts for Machine Learning Explained Simply</title>
               		<description><![CDATA[A model is almost never 100% sure of anything. These 10 probability concepts explain how it makes decisions anyway.]]></description>
                	<link>https://www.kdnuggets.com/10-probability-concepts-for-machine-learning-explained-simply</link>
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                	<pubDate>Tue, 07 Jul 2026 12:00:36 +0000</pubDate>
                	<dc:creator><![CDATA[Kanwal Mehreen]]></dc:creator>
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                	<title>Data Scientists Are Becoming AI Managers, Not Model Builders</title>
               		<description><![CDATA[The role is shifting from building models to managing them.]]></description>
                	<link>https://www.kdnuggets.com/data-scientists-are-becoming-ai-managers-not-model-builders</link>
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                	<pubDate>Mon, 06 Jul 2026 16:00:09 +0000</pubDate>
                	<dc:creator><![CDATA[Nate Rosidi]]></dc:creator>
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                	<title>Getting Started with Hugging Face ML Intern: Your First ML Agent</title>
               		<description><![CDATA[You describe the model. It writes the code, runs the training, and ships the checkpoint. Welcome to ML Intern.]]></description>
                	<link>https://www.kdnuggets.com/getting-started-with-hugging-face-ml-intern-your-first-ml-agent</link>
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                	<pubDate>Mon, 06 Jul 2026 14:00:31 +0000</pubDate>
                	<dc:creator><![CDATA[Kanwal Mehreen]]></dc:creator>
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