- This repository was initially created for the mind map; currently, it is used as a curated collection of software architecture references.
- This mind map is based on the Fresco Play curriculum (the internal learning platform of Tata Consultancy Services). © 2022
- Section 1: Software Architecture Mindmap
- Section 2: Software Architecture Reference
- Section 3: Computer Science Papers
- Section 4: Data Science (ML/NN)
- Section 5: Terminology and Comparisons
Software terminologies and concepts, software architecture overview
Software_Architecture_Mindmap.png: Application development, Cloud Computing, and Data science.
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- Awesome Engineering Articles: Curated high-quality engineering articles from top tech companies
- Awesome Lists: 🗂️Awesome lists about all kinds of interesting topics /
awesome.re/ github topic - awesome - Awesome Low Level Design (LLD) / Object Oriented Design (OOD)
- Awesome Software Architecture: A curated list of awesome articles, videos, and other resources to learn and practice software architecture, patterns, and principles
- Awesome Software Architecture (simskij)
- Awesome System Design Resources
- Ecosyste.ms: Awesome: An open API service indexing awesome lists
- Microsoft Learn: 🪟Microsoft documentation, tutorials, and code samples
- Microsoft .NET Application Architecture - Reference Apps
- Software Architecture Books: A comprehensive list of books on Software Architecture
- Software Architecture Books
- System Design: Learn how to design systems at scale and prepare for system design interviews
- System Design - Neo Kim
- System Design 101: 🗺️ByteByteGo
- System Design Fight Club
- Gartner Top Strategic Technology Trends 2024
- Google DORA: DevOps Research and Assessment (DORA)
- Hype Cycle for Emerging Technologies 2024
- MAD (ML/AI/Data) Landscape
- Microsoft Digital Defense Report
- Postman State of the API Report
- Software Industry Statistics: Statista Industry Insight
- Stanford AI Index Annual Report
- Dzone: RefCards and Trend Reports
- InfoQ: News and Articles
- InfoQ Trends Reports: đź“–(Downloaded PDFs 2019 and 2021 - 2025)
- Thoughtworks: Technology Radar đź“–(Downloaded PDFs vo.1 - vol.34)
- Trendshift: GitHub Trending repositories
- daily.dev: Personalized news feed
- Hacker News
- Substack Leaderboard: Newsletter
- AI agent orchestration patterns
- AWS to Azure services comparison
- Azure Architecture Center :AAC: architecture patterns and reference architectures
- Azure Cloud Adoption Framework :CAF: organization-wide adoption guidance
- Azure FinOps Guide
- Azure Well-architected Framework :WAF: workload-focussed design and continuous improvement guidance
- Best practices in cloud applications: Azure application architecture
- Cloud Design Patterns
- Compare AWS and Azure services to Google Cloud
- Data partitioning strategies
- Google Cloud to Azure services comparison
- Landing zone
- Microsoft Azure Developer's Cheat Sheet: Every product, feature and service in the Azure family
- Modern Web App pattern for .NET / GitHub
- Resources for architects and developers of multitenant solutions
- 79 Engineering Blogs To Level Up Your System Design Skills
- AWS Architecture Blog
- Azure Architecture Blog
- Discord Blog: Engineering & Developers
- Engineering at Meta
- GCP Cloud Blog
- LinkedIn Engineering
- Netflix TechBlog
- Slack Engineering
- Stripe Blog: Engineering
- The Cloudflare Blog
- Uber Blog
- Build frontend applications at scale
- Clone Wars: 100+ open-source clones of popular sites
- Curated list of project-based tutorials
- JavaScript Runtime from Scratch: C programming
- Let's Build a Simple Database: Writing a sqlite clone from scratch in C
- Let’s Build A Simple Interpreter
- Let’s Build A Web Server
- Master programming by recreating your favorite technologies from scratch
- minimal GPT
- PyTorch internals
- Web Browser Engineering: Building a basic but complete web browser from scratch
- Writing an Operating System in 1,000 Lines
- AI learning portals: Anthropic Academy, Google AI Training, Meta AI Resources, NVIDIA CUDA, Microsoft Learn, OpenAI Academy, IBM SkillsBuild, AWS Skill Builder, DeepLearning.AI, and Hugging Face Learn
- AI by Hand
- Best-of Machine Learning with Python: A ranked list of awesome machine learning Python libraries. Updated weekly.
- Computer Networking Fundamentals For Developers, DevOps, and Platform Engineers
- Computer Science courses with video lectures
- freeCodeCamp: Learn to code for free. youtube
- Introduction to CUDA Programming for Python Developers
- Kaggle Solutions and Ideas: Collection of Kaggle Solutions and Ideas
- Ultimate Collection of 60 YouTube Courses for 21 Programming Languages
- AI Agents for Beginners
- AI for Beginners
- Choose Your Own Copilot Adventure
- Cybersecurity for Beginners
- Data Science for Beginners
- Generative AI for Beginners
- Generative AI for Beginners using .NET
- IoT for Beginners
- Mastering GitHub Copilot for AI Paired Programming
- Mastering GitHub Copilot for C#/.NET Developers
- ML for Beginners
- Model Context Protocol (MCP) For Beginners
- Web Dev for Beginners
- XR Development for Beginners
- Agentic Architectures for Retrieval-intensive Applications
- Building a scalable authorization system
- Google SRE Handbook
- InfoQ Architectures You've Always Wondered About: đź“–(Downloaded PDFs 2021 - 2025)
- InfoQ Cell-Based Architecture
- Mastering AI Agents
- Mastering RAG
- Programming Notes for Professionals books
- System Design Blueprint: The Ultimate Guide
- Algorithm Visualizer: Interactive algorithm visualization
- Hello Algo: Algorithm tutorials
- Netron: Neural network visualizer
- Wikipedia: List of Algorithms: Comprehensive algorithm reference
- Best Kubernetes Tools: Curated Kubernetes tools by Bluelight Consulting
- Crontab Guru: Interactive cron schedule expression editor and reference
- Google Engineering Practices Documentation
- How To Secure A Linux Server
- PostgreSQL Wiki: Don't Do This: Common PostgreSQL pitfalls
- Power BI DAX Patterns: Patterns and best practices for Power BI DAX
- Robin Wieruch Blog: React.js, Next.js, TypeScript, JavaScript libraries, and trends
- Wise Tech Stack: Platform engineering practices across Kubernetes, delivery, data, AI, and observability
- Data Engineering Wiki: Data engineering resources and guides
- Dev Encyclopedia: Encyclopedia for developers (GitHub)
- OOP Design Patterns: Object-oriented design patterns explained
- Paperdraw: System Design Simulator
- Excalidraw: Hand-drawn style diagrams
- Eraser.io: Diagramming as code
- GraphViz: Graph visualization
- Mermaid Diagram: Diagramming and charting tool
- PlantUML: UML diagrams
- Ask R Discovery: AI-powered paper discovery tool
- Connected Papers: Explore connected academic papers
- Liner: AI research tool for highlighting and annotating
- Litmaps: Visualize relationships between research papers
- Moonlight: Browser extension for academic research
- scite_: Smart citation analysis and discovery
- Semantic Scholar: AI-powered academic search engine
- Attention Is All You Need: Transformer architecture based on self-attention
- How Top AI Labs Are Building RL Agents in 2026: RLHF, verifiable rewards, GRPO, and LLM-as-a-judge reward signals for agent training
- Interactive Reinforcement Learning Explorer
- LLM Architecture Gallery
- LLM Visualization
- The Illustrated Transformer
- Transformer Explainer
- Why Momentum Really Works
- Assembly code visualizer: Visualize Your Assembly Code
- explorar.dev: Explore curated open-source repositories with an interactive code browser.
- Idea Instructions: Complex concepts explained as IKEA-style visual instructions
- Linux Kernel Map: Interactive visual map of the Linux kernel subsystems
- Making Software: Visual explanations of how software works under the hood
- Understanding the Linux Kernel, Visually
- .NET Developer Roadmap
- A periodic table for machine learning:🔬A visual guide to machine learning concepts and techniques
- Celebrate 50 years of Microsoft with the company's original source code: Altair Basic
- Every GPU — Data Viz: Visual comparison of GPU specs and performance across generations
- Frugal Architect Handbook
- Generative Search: Practical Advice for Retrieval Augmented Generation (RAG)
- How to Architect Software for a Greener Future
- What are the Greenest Programming Languages?
- Code Complete by Steve McConnell
- Modern Software Engineering by David Farley
- Software Engineering at Google by Titus Winters, Tom Manshreck, and Hyrum Wright
- The Pragmatic Programmer by David Thomas and Andrew Hunt
- Clean Code by Uncle Bob Martin
- Design Patterns by Eric Gamma and Others
- Head First Design Patterns by Eric Freeman
- Refactoring by Martin Fowler
- Cracking the Coding Interview by Gayle Laakmann McDowell
- Grokking Algorithms by Aditya Bhargava
- Introduction to Algorithms by Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, Clifford Stein
- Designing Data-Intensive Applications by Martin Kleppman
- Learning SQL by Alan Beaulieu
- Growing Object-Oriented Software, Guided by Tests by Steve Freeman
- The Art of Unit Testing by Roy Osherove
- TDD by Example by Kent Beck
- Unit Testing Principles, Practices, and Patterns by Vladimir Khorikov
- A Philosophy of Software Design by John Ousterhout
- Clean Architecture by Uncle Bob Martin
- Domain-Driven Design by Eric Evans
- Domain-Driven Design Quickly by Abel Avram and Floyd Marinescu
- Fundamentals Of Software Architecture by Mark Richards and Neil Ford
- Software Architecture: The Hard Parts by Neal Ford, Mark Richards, Pramod Sadalage, and Zhamak Dehghani
- System Design Interview by Alex Xu
- Designing Distributed Systems by Brendan Burns
- Understanding Distributed Systems by Roberto Vitillo
- Accelerate by Nicole Forsgren, Jez Humble, and Gene Kim
- Continuous Delivery by Jez Humble and David Farley
- DevOps Handbook by Gene Kim, Patrick Debois, John Willis, and Jez Humble
- AI Engineering by Chip Huyen / GitHub
- Designing Machine Learning Systems by Chip Huyen
- The Hundred-Page Machine Learning Book by Andriy Burkov
- đź“–Downloaded PDFs - 12 files | Study notes
- An Axiomatic Basis for Computer Programming (1969): C.A.R. Hoare
- A Metrics Suite for Object-Oriented Design (1994): S.R. Chidamber
- A Note On Distributed Computing (1994): J. Waldo, G. Wyant, A. Wollrath, S. Kendall
- A Relational Model of Data for Large Shared Data Banks (1969): E.F. Codd
- Dynamo: Amazon’s Highly Available Key-value Store (2007): G. DeCandia et al.
- MapReduce: Simplified Data Processing on Large Clusters (2004): J. Dean, S. Ghemawat
- On the Criteria To Be Used in Decomposing Systems into Modules (1972): D.L. Parnas
- Out of the Tar Pit (2006): B. Moseley, P. Marks
- Time, Clocks, and the Ordering of Events in a Distributed System (1978): L. Lamport
- Transmission Control Protocol (1981): J. Postel | A TCP/IP Tutorial (1991): a tutorial on the TCP/IP protocol
- Why Functional Programming Matters (1990): J. Hughes
- đź“–Downloaded PDFs - 25 files | Study notes
- Amazon Aurora: How Amazon provides high availability and performance
- Attention Is All You Need: Into a new deep learning architecture known as the transformer
- BigTable: The design principles behind a distributed storage system
- Bitcoin: The ground-breaking introduction to the peer-to-peer electronic cash system
- Borg: Large Scale Cluster Management at Google
- Cassandra: A look at the design and architecture of a distributed NoSQL database
- Dapper: Insights into Google’s distributed systems tracing infrastructure
- Dynamo: Amazon’s Highly Available Key Value Store
- Flink: A detailed look at the unified architecture of stream and batch processing
- FoundationDB: A look at how a distributed database works
- Google File System: Insights into a highly scalable file system
- GoTo Considered Harmful
- Kafka: Internals of the distributed messaging platform
- MapReduce: A detailed look at how MapReduce enables parallel processing of massive volumes of data
- Monarch: Architecture of Google’s in-memory time series database
- MyRocks: LSM-Tree Database Storage Engine
- Raft Consensus Algorithm: Learn about the more understandable consensus algorithm
- Scaling Memcached at Facebook: A look at the complexities of caching
- Shard Manager: Understanding the generic shard management framework
- Spanner: Design and architecture of Google’s globally distributed database
- Thrift: Explore the design choices behind Facebook’s code-generation tool
- Time Clocks and Ordering of Events: The extremely important paper that explains the concept of time and event ordering in a distributed system
- WTF - Who to Follow Service at Twitter: Twitter’s (now X) user recommendation system
- Zanzibar: A look at the design, implementation, and deployment of a global system for managing access control lists at Google
- The best NLP papers: 🔬A curated collection of influential NLP papers
- đź“–Downloaded PDFS - 100 files | Study notes
- Here's a reading list of 70+ Distributed Systems papers mostly from conferences in just last 2 years! 70+ Distributed Systems papers [Jan 2024]
- đź“–Downloaded PDFS - 72 files | Study notes
- Awesome Math Books
- Free eBooks for ML, Data Science & AI
- ML and LLM system design: A database of 800 case studies from 150+ companies.
- Approaching (Almost) Any ML Problem – Abhishek Thakur
- Deep Learning – Ian Goodfellow, Yoshua Bengio, Aaron Courville
- Dive into Deep Learning – Aston Zhang et al.
- Hands-On Machine Learning with R – Boehmke & Greenwell
- Machine Learning Engineering – Andriy Burkov
- Machine Learning for Humans – Vishal Maini, Samer Sabri
- Machine Learning For Dummies – Judith Hurwitz, Daniel Kirsch
- Machine Learning Systems: Introduction to Machine Learning Systems – Vijay Janapa Reddi
- Machine Learning Yearning – Andrew Ng
- The Hundred-Page Machine Learning Book – Andriy Burkov
- Understanding Machine Learning – Shai Shalev-Shwartz, Shai Ben-David
- @mathtalent Lecture Notes – Math-focused CS notes
- Algebra, Topology, Calculus & Optimization for CS/ML – Jean Gallier
- Algorithms for Artificial Intelligence – Moss
- An Introduction to Statistical Learning – James et al.
- Calculus for Mathematicians, Computer Scientists, and Physicists – Andrew D. Hwang
- Information Theory, Inference, and Learning Algorithms – David J. C. MacKay
- Math Foundations for Computer Science – Stanford CS103
- Mathematical Methods for CV, Robotics, Graphics – Stanford
- Mathematics for Machine Learning – Deisenroth, Faisal, Ong
- Pattern Recognition and ML – Christopher Bishop
- The Elements of Statistical Learning – Friedman, Tibshirani, Hastie
- A Brief Introduction to ML for Engineers – Osvaldo Simeone
- Applied Causal Inference – Uday Kamath et al.
- Automated Machine Learning – Frank Hutter et al.
- Boosting: Foundations and Algorithms – Schapire & Freund
- Computer Vision: Models, Learning, and Inference – Simon J.D. Prince
- Deep Learning on Graphs – Yao Ma & Jiliang Tang
- Deep Learning Interviews – Shlomo Kashani, Amir Ivry
- Feature Engineering and Selection – Max Kuhn & Kjell Johnson
- Interpretable Machine Learning – Christoph Molnar
- ML Interpretability – Patrick Hall & Navdeep Gill
- Natural Language Processing with Python – Bird, Klein, Loper
- Probabilistic ML: Advanced Topics – Kevin P. Murphy
- Probabilistic ML: An Introduction – Kevin P. Murphy
- Reinforcement Learning: An Introduction – Sutton & Barto
- Speech and Language Processing – Jurafsky & Martin
- Awesome Data Science
- Awesome Machine Learning
- Data Science Python Notebooks
- Interactive Educational Data Science Python Dashboards
- Machine Learning for Beginners – Microsoft
- Open Source Data Science Masters
- Python Data Science Handbook
- The Data Engineering Handbook
- Virgilio – Data Science Curriculum
- Deep Learning Book (MIT)
- Deep Learning Models by Rasbt
- fastai Book (fastbook) | Fast.ai courses
- labml.ai – Deep Learning Paper Implementations
- Mathematics for Machine Learning
- 365 Data Science Flashcards
- Applied ML – Papers & Blogs
- Awesome Production Machine Learning
- Data Science Project Template (Cookiecutter)
- Machine Learning Tutorials
- Machine Learning ZoomCamp
- openpilot – Driver Assistance System
- Machine Learning Mastery by Jason Brownlee
- Papers With Code:🔬Research papers with code, datasets, and benchmarks
- StatQuest by Josh Starmer
- See Glossary.md: an overview of key terminology, definitions, and comparisons between related concepts.