David Park's repositories
50-DAYS-OF-DEEP-LEARNING
Welcome to the Deep Learning 50 Days Challenge repository! This repository contains resources, code samples, and projects for a comprehensive 50-days deep learning journey.
architecture-center
Open Source documentation for the Azure Architecture Center on Microsoft Docs
awesome-azure-architecture
AWESOME-Azure-Architecture - https://aka.ms/AwesomeAzureArchitecture
awesome-productivity
A curated list of delightful productivity resources.
Awesome-Prompt-Engineering
This repository contains a hand-curated resources for Prompt Engineering with a focus on Generative Pre-trained Transformer (GPT), ChatGPT, PaLM etc
awesome-reMarkable
A curated list of projects related to the reMarkable tablet
Blogs_Content
Contains Google Colab or Jupyter notebooks, as well as other associated files for my Medium blogposts.
courtlistener
A fully-searchable and accessible archive of court data including growing repositories of opinions, oral arguments, judges, judicial financial records, and federal filings.
create-tsi
Create-tsi is a generative AI RAG toolkit which generates AI Applications with low code.
data-science
:bar_chart: Path to a free self-taught education in Data Science!
Data-Structure-Algorithms-LLD-HLD
A Data Structure Algorithms Low Level Design and High Level Design collection of resources.
easy-random
The simple, stupid random Java beans/records generator
engineering-blogs
A curated list of engineering blogs
Enterprise-Scale
The Azure Landing Zones (Enterprise-Scale) architecture provides prescriptive guidance coupled with Azure best practices, and it follows design principles across the critical design areas for organizations to define their Azure architecture
jailbreak_llms
[CCS'24] A dataset consists of 15,140 ChatGPT prompts from Reddit, Discord, websites, and open-source datasets (including 1,405 jailbreak prompts).
latex-yearly-planner
Digital planner for Supernote and ReMarkable // Support Ukraine 🇺🇦 https://savelife.in.ua/en
learn-generative-ai
Learn Cloud Applied Generative AI Engineering (GenEng) using OpenAI, Gemini, Streamlit, Containers, Serverless, Postgres, LangChain, Pinecone, and Next.js
llm-course
Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.
llm-datasets
High-quality datasets, tools, and concepts for LLM fine-tuning.
local-genAI-search
Local-GenAI-Search is a generative search engine based on Llama 3, langchain and qdrant that answers questions based on your local files
localstack
💻 A fully functional local AWS cloud stack. Develop and test your cloud & Serverless apps offline!
semantic-kernel
Integrate cutting-edge LLM technology quickly and easily into your apps
studio-lab-examples
Example notebooks for working with SageMaker Studio Lab. Sign up for an account at the link below!
summary-of-a-haystack
Codebase accompanying the Summary of a Haystack paper.
system-design
Learn how to design systems at scale and prepare for system design interviews
system-design-101
Explain complex systems using visuals and simple terms. Help you prepare for system design interviews.
what-happens-when
An attempt to answer the age old interview question "What happens when you type google.com into your browser and press enter?"