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tungwini
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Algorithms and Data Structures implemented in Go for beginners, following best practices.
Deploy your AI/ML model to Amazon SageMaker for Real-Time Inference and Batch Transform using your own Docker container image.
A curated awesome list of lists of interview questions. Feel free to contribute! 🎓
💯 Curated coding interview preparation materials for busy software engineers
📝 Algorithms and data structures implemented in JavaScript with explanations and links to further readings
🌐 Front End interview preparation materials for busy engineers (updated for 2025)
Everything you need to prepare for your technical interview
A complete computer science study plan to become a software engineer.
Learn how to design large-scale systems. Prep for the system design interview. Includes Anki flashcards.
Examples and guides for using the OpenAI API
An automatic evaluator for instruction-following language models. Human-validated, high-quality, cheap, and fast.
Code for loralib, an implementation of "LoRA: Low-Rank Adaptation of Large Language Models"
AutoGPT is the vision of accessible AI for everyone, to use and to build on. Our mission is to provide the tools, so that you can focus on what matters.
CLI platform to experiment with codegen. Precursor to: https://lovable.dev
A playbook for systematically maximizing the performance of deep learning models.
Python 开源项目之「自学编程之路」，保姆级教程：AI实验室、宝藏视频、数据结构、学习指南、机器学习实战、深度学习实战、网络爬虫、大厂面经、程序人生、资源分享。
The open source version of the Amazon SageMaker docs
A hub for all of my generative art projects
Content Repository for Kinesis lab
Build, train & debug, and deploy & monitor with Amazon SageMaker
Learn how to manage, process, host, and authorize access to streaming video content by building UnicornFlix
😈 Dynamon is GUI client for DynamoDB, can connect local dynamodb.
A library you can include in your Spark job to validate the counters and perform operations on success. Goal is scala/java/python support.
Examples for High Performance Spark
Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.
VIP cheatsheets for Stanford's CS 229 Machine Learning