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