Lisa Notes
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Lisa Notes

Lisa's notes: musings on daily life, work, study, personal growth, and casual reflections.

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Latest from Lisa Notes

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Lisa Notes
Lisa Notes
Jul 5, 2026 · R&D Management

Understanding the Stage‑Gate Process Through IPD: A Study Note

The article explains the Stage‑Gate System (SGS) and its IPD‑based implementation, detailing its core concepts, the distinction between "doing the right project" and "doing the project right", and the four foundational ideas that make the process flexible, reusable, and structured for effective product development.

Cross-functional TeamsIPDProcess Flexibility
0 likes · 8 min read
Understanding the Stage‑Gate Process Through IPD: A Study Note
Lisa Notes
Lisa Notes
Jul 4, 2026 · Fundamentals

Using Interfaces as Types in Java: A Beginner’s Guide

This note explains how Java interfaces define new data types, how variables of an interface type must reference objects implementing that interface, and demonstrates the concept with a concrete example that casts objects to a Compare interface to select the larger one.

CastingInterfaceJava
0 likes · 3 min read
Using Interfaces as Types in Java: A Beginner’s Guide
Lisa Notes
Lisa Notes
Jul 4, 2026 · Artificial Intelligence

NLP Study Notes: Methods for Natural Language Processing Using Pre‑trained Models

This article reviews the evolution of deep learning, its key concepts, model architectures, training strategies, and applications—especially in speech, vision, and natural language processing—highlighting seminal research, comparative analyses, and current challenges for future AI development.

AIDeep LearningNLP
0 likes · 77 min read
NLP Study Notes: Methods for Natural Language Processing Using Pre‑trained Models
Lisa Notes
Lisa Notes
Jul 4, 2026 · R&D Management

IPD Learning Notes: How PACE (Product & Cycle‑time Excellence) Shapes Integrated Product Development

The article explains PACE—Product and Cycle‑time Excellence—originating from PRTM in 1986, outlines its seven core principles, details its seven‑factor system of four project‑level and three cross‑project elements, and shows how the framework guides structured, collaborative product development within IPD.

IPDPACEProduct Development
0 likes · 6 min read
IPD Learning Notes: How PACE (Product & Cycle‑time Excellence) Shapes Integrated Product Development
Lisa Notes
Lisa Notes
Jul 3, 2026 · Artificial Intelligence

NLP Study Notes: How Deep Learning Powers Natural Language Processing

This article explains how deep learning models such as RNN, LSTM, GRU and Transformer enable NLP tasks like machine translation, text classification, question answering and text generation, outlines their advantages over traditional methods, and provides a Keras code example for text classification.

Deep LearningKerasMachine Translation
0 likes · 8 min read
NLP Study Notes: How Deep Learning Powers Natural Language Processing
Lisa Notes
Lisa Notes
Jul 3, 2026 · Product Management

IPD Study Notes: Cultivating Product Managers from an IPD R&D Perspective

This article examines the distinction between project and product managers, outlines the high‑standard qualities required of product managers, describes the ideal career pathways and ability models, and details a resource‑pool framework for systematically developing product‑manager talent within an IPD‑driven R&D organization.

IPDProduct ManagementR&D
0 likes · 21 min read
IPD Study Notes: Cultivating Product Managers from an IPD R&D Perspective
Lisa Notes
Lisa Notes
Jul 3, 2026 · Fundamentals

Java Interface Implementation: A Step‑by‑Step Tutorial from Scratch

This tutorial walks through Java interface basics, showing how to declare an interface, implement it in classes, handle method and constant conflicts when implementing multiple interfaces, and demonstrates the concepts with concrete Rectangle and Circle examples.

Code ExampleInterfaceJava
0 likes · 10 min read
Java Interface Implementation: A Step‑by‑Step Tutorial from Scratch
Lisa Notes
Lisa Notes
Jul 2, 2026 · Artificial Intelligence

NLP Study Notes: How Pre‑trained Models Transform Language Processing

This article reviews the evolution of pre‑trained models in natural language processing, from early word embeddings to Transformer‑based architectures like BERT and its variants, outlines their wide‑range applications such as QA, translation, and dialogue, and discusses remaining challenges and future research directions.

AIBERTNLP
0 likes · 6 min read
NLP Study Notes: How Pre‑trained Models Transform Language Processing