Resources  
  • Precision & Recall - Evaluation metrics To fine true positive PredictionMay 06, 2025. Precision and Recall are key evaluation metrics in machine learning that help measure how well a model identifies true positives.
  • RAG Fine Tuning and RAFT Explained Jun 04, 2024. In the realm of large language models (LLMs), techniques like in-context learning (ICL), retrieval augmented generation (RAG), fine-tuning, and retrieval augmented fine-tuning (RAFT) are revolutionizing how these models process information and generate responses. These techniques address key challenges such as scalability.
  • Database Fine Tuning - Best Practices And ExamplesFeb 10, 2023. In this article, you will learn about Database Fine Tuning - Best Practices and Examples.
  • Leadership Challenge 013 - Alan Fine - Breakthrough PerformanceJul 10, 2019. In this article you will learn about Alan Fine - Breakthrough Performance.
  • Fine-Tune or Tweak Prompts for Better AccuracySep 07, 2025. Discover proven strategies to fine-tune and tweak prompts for better accuracy in large language models (LLMs). Learn prompt optimization techniques, examples, and tools to refine outputs.
  • Fine-Tuning vs External Knowledge: What Works Best for Enterprise AI?Sep 05, 2025. Explore the crucial decision of fine-tuning vs. Retrieval-Augmented Generation (RAG) for enterprise AI. Understand when to leverage fine-tuning for deep domain knowledge and specific outputs, versus RAG for dynamic knowledge retrieval and rapid deployment. Discover the cost, flexibility, and data freshness implications of each approach to optimize your AI strategy and maximize ROI.
  • From Syntax to Semantics: Fine-Tuning NLP Models for Precision and PowerAug 18, 2025. Fine-tuning in NLP adapts large language models to specific tasks or domains using methods like full fine-tuning, prompt tuning, and LoRA, improving accuracy, efficiency, and real-world applicability.
  • Fine-Tuning Azure OpenAI Models with Domain-Specific DataDec 12, 2024. Learn how to fine-tune Azure OpenAI models with domain-specific data to enhance performance for industry-specific applications.
  • Fine-Tuning in Machine Learning Jul 31, 2024. This is one of the great techniques in machine learning, because it reused the pre-trained model and made it efficient for a new task with good accuracy. It also reduced the work of training a new model.
  • Learn Fine-Tuning Llama 3.1Jul 31, 2024. This article provides a step-by-step guide on fine-tuning the Llama 3.1 language model using Python and the Hugging Face Transformers library. It includes code examples, explanations, and best practices for achieving optimal performance.
  • Re-training is Fine-tuning: Yes or No?Jul 11, 2024. This content explores the nuances between re-training and fine-tuning in the context of machine learning and neural networks. It examines whether re-training can be considered a form of fine-tuning or if they are distinct processes.
  • Fine-Tuning Hyperparameters using Hyperdrive in Azure Machine Learning SDKJun 22, 2023.
  • How Do Large Language Models Work? A Deep Dive into LLM AIAug 19, 2025. Discover how Large Language Models (LLMs) like ChatGPT work, from their training lifecycle and Transformer architecture to challenges like bias, sustainability, and security. This in-depth guide explains the mechanics of LLMs, their impact on industries, and the future of Generative AI.
  • Should We Train Our Own LLMs or Use Existing Ones via APIs?Jun 13, 2025. Learn whether to train your own LLM or use existing APIs, with pros, cons, cost considerations, and expert tips to guide your enterprise AI strategy.
  • 🎥 Sentiment Analysis on IMDb Using BERT and Hugging FaceJun 05, 2025. Learn how to fine-tune BERT for sentiment analysis using the IMDb dataset with Hugging Face Transformers. Includes Python code, attention visualization, and Gradio deployment.
  • 📃 Text Summarization with T5 and Hugging Face TransformersJun 06, 2025. Learn how to build a text summarizer with T5 and Hugging Face. Step-by-step Python tutorial with code, Gradio interface, and fine-tuning tips.
  • Named Entity Recognition (NER) with spaCy and TransformersJun 06, 2025. Learn how to use Named Entity Recognition (NER) with spaCy and transformer models like BERT to extract people, places, and organizations from text with high accuracy.
  • How to create a Binary File in C#Jul 12, 2012. How to create and write to a binary fine using C# and .NET. The System.IO.BinaryWriter class is used to write binary data to a stream. This class also provides an option to specify the character encoding including ASCII, Unicode, UTF32, UTF7, and UTF8 encoding.
  • Delete Temporary Files in Windows 8Jun 07, 2012. This article describes how to delete temporary files in Windows 8.
  • PermissionSet Class In C# Mar 26, 2010. The PermissionSet class in C# is a fundamental component of .NET security that allows developers to encapsulate a set of permissions for code execution. It enables the definition and management of fine-grained permissions required by an application to access various system resources and perform specific operations. With PermissionSet, developers can control actions like file operations, registry access, and network communication within the application's security context. By specifying the permissions a code segment needs, developers can enforce security policies, ensuring that the application runs securely and only performs authorized actions.
  • Oracle Data Provider for .NET : Part IVFeb 20, 2004. Oracle Data Provider for .NET (ODP.NET) is an implementation of a data provider for the Oracle database. ODP.NET uses Oracle native APIs to offer fast and reliable access to Oracle data and features from any .NET application.