<?xml version="1.0" encoding="UTF-8"?>
<rss version="2.0" 
    xmlns:atom="http://www.w3.org/2005/Atom" 
    xmlns:media="http://search.yahoo.com/mrss/"
    xmlns:dc="http://purl.org/dc/elements/1.1/">
    <channel>
        <title>MachineLearningMastery.com</title>
        <link>https://machinelearningmastery.com/</link>
        <description>Making developers awesome at machine learning</description>
        <atom:link href="https://machinelearningmastery.com/feed/" rel="self" type="application/rss+xml" />
            	<item>
                	<title>How to Train Your own Decision Model like Jev using Unsloth</title>
               		<description><![CDATA[In this article, you will learn how to turn an open-weight language model into a decision model that classifies user intent, by fine-tuning Qwen3.5-4B on...]]></description>
                	<link>https://machinelearningmastery.com/how-to-train-your-own-decision-model-like-jev-using-unsloth/</link>
                	<guid isPermaLink="false">https://machinelearningmastery.com/?p=25706</guid>
                	<pubDate>Wed, 04 Nov 2026 11:00:00 +0000</pubDate>
                	<dc:creator><![CDATA[Kanwal Mehreen]]></dc:creator>
                	<media:content url="https://machinelearningmastery.com/wp-content/uploads/2026/11/mlm-how-to-train-your-own-decision-model-like-jev-using-unsloth-feature.png" medium="image" />
		</item>
            	<item>
                	<title>Choosing an LLM Inference Optimization Technique: A Decision-Tree Approach</title>
               		<description><![CDATA[In this article, you will learn how to match an LLM inference optimization technique to the actual bottleneck in your workload by working through a...]]></description>
                	<link>https://machinelearningmastery.com/choosing-an-llm-inference-optimization-technique-a-decision-tree-approach/</link>
                	<guid isPermaLink="false">https://machinelearningmastery.com/?p=25412</guid>
                	<pubDate>Tue, 03 Nov 2026 11:00:00 +0000</pubDate>
                	<dc:creator><![CDATA[Bala Priya C]]></dc:creator>
                	<media:content url="https://machinelearningmastery.com/wp-content/uploads/2026/09/mlm-inference-optimization-decision-tree-cover.png" medium="image" />
		</item>
            	<item>
                	<title>The AI Agent Memory Stack: Building Blocks, Patterns, and Frameworks</title>
               		<description><![CDATA[In this article, you will learn how agent memory works, what types of memory exist, and how different frameworks approach storage, retrieval, and memory management...]]></description>
                	<link>https://machinelearningmastery.com/the-ai-agent-memory-stack-building-blocks-patterns-and-frameworks/</link>
                	<guid isPermaLink="false">https://machinelearningmastery.com/?p=25424</guid>
                	<pubDate>Mon, 02 Nov 2026 11:00:00 +0000</pubDate>
                	<dc:creator><![CDATA[Bala Priya C]]></dc:creator>
                	<media:content url="https://machinelearningmastery.com/wp-content/uploads/2026/09/mlm-bala-agent-memory-stack.png" medium="image" />
		</item>
            	<item>
                	<title>7 Ways Your AI Agent Is Wasting Tokens (And What to Do Instead)</title>
               		<description><![CDATA[In this article, you will learn seven common token-waste patterns in production AI agent systems, and the architectural fixes that address each one. Topics we...]]></description>
                	<link>https://machinelearningmastery.com/7-ways-your-ai-agent-is-wasting-tokens-and-what-to-do-instead/</link>
                	<guid isPermaLink="false">https://machinelearningmastery.com/?p=25352</guid>
                	<pubDate>Fri, 30 Oct 2026 11:00:00 +0000</pubDate>
                	<dc:creator><![CDATA[Vinod Chugani]]></dc:creator>
                	<media:content url="https://machinelearningmastery.com/wp-content/uploads/2026/09/mlm-chugani-7-ways-ai-agent-wasting-tokens-feature.png" medium="image" />
		</item>
            	<item>
                	<title>Fine-Tuning vs. Frozen Embeddings: When to Adapt the LLM vs. the Sklearn Head</title>
               		<description><![CDATA[In this article, you will learn how to compare two strategies for adapting a large language model to a specific domain: fine-tuning with LoRA versus...]]></description>
                	<link>https://machinelearningmastery.com/fine-tuning-vs-frozen-embeddings-when-to-adapt-the-llm-vs-the-sklearn-head/</link>
                	<guid isPermaLink="false">https://machinelearningmastery.com/?p=25044</guid>
                	<pubDate>Wed, 28 Oct 2026 11:00:00 +0000</pubDate>
                	<dc:creator><![CDATA[Iván Palomares Carrascosa]]></dc:creator>
                	<media:content url="https://machinelearningmastery.com/wp-content/uploads/2026/10/mlm-fine-tuning-vs-frozen-embeddings-when-to-adapt-the-llm-vs-the-sklearn-head-feature.png" medium="image" />
		</item>
            	<item>
                	<title>Context Managers Beyond Opening Files in Python</title>
               		<description><![CDATA[The stopwatch in the opening script is the smallest case of the pattern.]]></description>
                	<link>https://machinelearningmastery.com/context-managers-beyond-opening-files/</link>
                	<guid isPermaLink="false">https://machinelearningmastery.com/?p=25656</guid>
                	<pubDate>Tue, 27 Oct 2026 11:00:00 +0000</pubDate>
                	<dc:creator><![CDATA[Nahla Davies]]></dc:creator>
                	<media:content url="https://machinelearningmastery.com/wp-content/uploads/2026/10/mlm-context-managers-beyond-opening-files-feature.png" medium="image" />
		</item>
            	<item>
                	<title>Robust Serialization with JSON and Custom Types</title>
               		<description><![CDATA[In this article, you will learn how to build a robust JSON serialization pipeline in Python that handles custom data types, graceful error recovery, and...]]></description>
                	<link>https://machinelearningmastery.com/robust-serialization-with-json-and-custom-types/</link>
                	<guid isPermaLink="false">https://machinelearningmastery.com/?p=25365</guid>
                	<pubDate>Mon, 26 Oct 2026 11:00:00 +0000</pubDate>
                	<dc:creator><![CDATA[Iván Palomares Carrascosa]]></dc:creator>
                	<media:content url="https://machinelearningmastery.com/wp-content/uploads/2026/10/mlm-robust-serialization-with-json-and-custom-types-feature.png" medium="image" />
		</item>
            	<item>
                	<title>Speculative Decoding Explained: How to Get 3× Faster Inference from Any LLM</title>
               		<description><![CDATA[In this article, you will learn how speculative decoding works, why it produces real speed gains at the hardware level, and what modern implementations look...]]></description>
                	<link>https://machinelearningmastery.com/speculative-decoding-explained-how-to-get-3x-faster-inference-from-any-llm/</link>
                	<guid isPermaLink="false">https://machinelearningmastery.com/?p=25359</guid>
                	<pubDate>Fri, 23 Oct 2026 11:00:00 +0000</pubDate>
                	<dc:creator><![CDATA[Vinod Chugani]]></dc:creator>
                	<media:content url="https://machinelearningmastery.com/wp-content/uploads/2026/09/mlm-chugani-speculative-decoding-3x-faster-inference-llm-feature.png" medium="image" />
		</item>
            	<item>
                	<title>How to Build a Multi-Modal RAG Pipeline for Images and Documents in Python</title>
               		<description><![CDATA[In this article, you will learn how to build a multi-modal RAG pipeline in Python that retrieves and reasons over both text and images extracted...]]></description>
                	<link>https://machinelearningmastery.com/how-to-build-a-multi-modal-rag-pipeline-for-images-and-documents-in-python/</link>
                	<guid isPermaLink="false">https://machinelearningmastery.com/?p=25407</guid>
                	<pubDate>Wed, 21 Oct 2026 11:00:00 +0000</pubDate>
                	<dc:creator><![CDATA[Vinod Chugani]]></dc:creator>
                	<media:content url="https://machinelearningmastery.com/wp-content/uploads/2026/09/mlm-chugani-multi-modal-rag-pipeline-images-documents-python-feature.png" medium="image" />
		</item>
            	<item>
                	<title>pgvector vs. Dedicated Vector Databases: A Production Benchmark</title>
               		<description><![CDATA[Run this on a typical laptop and both systems will report latencies in the low single-digit to tens of milliseconds range, with the exact numbers depending heavily on your CPU, available RAM, and whatever else is running on your machine at the time.]]></description>
                	<link>https://machinelearningmastery.com/pgvector-vs-dedicated-vector-databases-a-production-benchmark/</link>
                	<guid isPermaLink="false">https://machinelearningmastery.com/?p=25330</guid>
                	<pubDate>Tue, 20 Oct 2026 11:00:00 +0000</pubDate>
                	<dc:creator><![CDATA[Shittu Olumide]]></dc:creator>
                	<media:content url="https://machinelearningmastery.com/wp-content/uploads/2026/09/MLM-Shittu-pgvector-vs.-Dedicated-Vector-Databases-A-Production-Benchmark-scaled.png" medium="image" />
		</item>
        </channel>
</rss>