Advanced Prompt Engineering Techniques for Building AI-Powered Systems

Understanding and Implementing Prompt Engineering Prompt engineering, also known as instruction engineering, is the practice of designing and refining input prompts to guide large language models (LLMs) toward generating desired outputs. It involves crafting precise instructions that leverage the model's capabilities to solve specific problems ...

Posted on Mon, 17 Aug 2026 16:32:23 +0000 by mady

Visualizing Naive Bayes with Confidence Ellipses

This lab explores Naive Bayes features by visualizing tweet sentiment data, focusing on the log-likelihood ratio as a numeric feature for machine learning. We also introduce confidence ellipses as a tool to intuitively represent the Naive Bayes model. Imports import numpy as np import pandas as pd import matplotlib.pyplot as plt from utils impo ...

Posted on Sat, 08 Aug 2026 16:21:26 +0000 by BigJohn

Understanding the forward() Method of Hugging Face's BertModel

BertModel Forward Computation Overview The forward() method in Hugging Face's BertModel executes the forward pass through the Transformer architecture too generate contextualized token representations. This base model outputs raw hidden states without task-specific heads, making it ideal for text embedding extraction and feature analysis. Metho ...

Posted on Thu, 09 Jul 2026 16:48:51 +0000 by lutzlutz896

Building an AI-Powered SQL Generator with Spring Boot and LLM Integration

Understanding Large Language Models Large Language Models (LLMs) represent a significant advancement in artificial intelligence, characterized by their massive parameter counts and extensive training on diverse datasets. These models excel at understanding and generating human language, making them ideal for tasks requiring natural language com ...

Posted on Sun, 14 Jun 2026 18:13:02 +0000 by nikifi

Text Matching with LSTM in PyTorch

Text matching aims to determine whether two input sequences are semantical related or similar. This is commonly used in applications like question answering, duplicate dteection, and information retrieval. A typical approach involves encoding each sentence independently using recurrent neural networks such as LSTM, then comparing their final re ...

Posted on Thu, 04 Jun 2026 17:23:38 +0000 by ggseven

Prompt Engineering: Crafting Effective Instructions for Large Language Models

Core Principles of Prompt Engineering Two fundamental principles guide effective prompt construction: clarity and specificity combined with allocating sufficient processing time for the model to reason through complex tasks. Delimiters and Input Organization Delimiters serve as explicit boundaries within prompts, separating instructions from i ...

Posted on Sat, 09 May 2026 09:08:59 +0000 by ben2005

Text Similarity Analysis Implementation and Testing

Project Information Course Repository Link Software Engineering Project Repo Objective Build a basic engineering project Personal Software Process (PSP) Summary Stage Task Description Estimated (Min) Actual (Min) ...

Posted on Fri, 08 May 2026 10:30:38 +0000 by amarquis