TensorArcade — The Definitive Machine Learning, GenAI & MLOps Roadmap Hub

From First-Principles Mathematics & Classical Algorithms to Autonomous Agentic AI, High-Throughput MLOps, and FAANG Applied Scientist System Design.

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🎯 Overview

TensorArcade is a comprehensive, open-access Machine Learning curriculum and curated knowledge repository wrapped in a retro-arcade engineering aesthetic.

Synthesizing curricula from:

• roadmap.sh/machine-learning
• github.com/aadi1011/AI-ML-Roadmap-from-scratch
• Top University Lecture Series (MIT OCW, Stanford Online, Harvard)
• Senior Tech Leaders & FAANG Applied Scientists (Meta, Google, Netflix)
• The 2026 Foundation Model & Agentic AI Stack

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🕹️ Core Highlights & Features

1. 11-Stage Progressive Curriculum Tree

Interactive milestone checkboxes that persist progress to localStorage and award gamified XP:

• Stage 00: Environment & Foundations (Python 3.12+, VS Code, UV, Linux CLI, Git)
• Stage 01: The Mathematics Engine (Linear Algebra, Matrix Calculus, Probability, Optimization)
• Stage 02: Scientific Python & Data Science (NumPy vectorization, Pandas, Polars, SQL)
• Stage 03: Classical Machine Learning (Supervised, Unsupervised, Ensembles, XGBoost/LightGBM)
• Stage 04: Deep Learning & Neural Networks (Perceptrons, Autograd, CNNs, RNNs, PyTorch)
• Stage 05: Transformers & Modern NLP (Self-Attention, BERT, GPT from scratch, Hugging Face)
• Stage 06: Computer Vision & Multimodal AI (ViT, CLIP, YOLOv8, Latent Diffusion models)
• Stage 07: Generative AI & LLM Systems (PEFT/LoRA, RAG Pipelines, Vector DBs, vLLM)
• Stage 08: Agentic AI & AgentOps (ReAct loop, Tool Calling, LangGraph, Multi-Agent, MCP)
• Stage 09: Production MLOps & AI SecOps (Docker, Kubernetes, MLflow, Triton, Prompt Injection defense)
• Stage 10: FAANG Applied Scientist & MLE Blueprint (Interview archetypes, 7-Step ML System Design)

2. Curated Resource Matrix (Search & Filter)

• 120+ Vetted Masterworks: Video courses, textbooks, research papers, and practitioner code repos.
• Instant Search & Real-Time Filter: Search by algorithm, author, or keyword (press / to search).
• Deep Dive Modals: Inspect complete syllabi, prerequisites, and learning objectives.

3. Portfolio Project Quest Vault (4 Difficulty Tiers)

Detailed blueprints with architecture specs, datasets, and copy-paste resume bullets:

• 🌱 Tier 1: Beginner: Tabular Stacking Pipeline, Churn & SHAP Risk Engine, PyTorch Vision Classifier with Grad-CAM.
• ⚡ Tier 2: Intermediate: CLIP Semantic Search Engine, NanoGPT from scratch, Real-time YOLOv8 + TensorRT streaming.
• 🔥 Tier 3: Advanced: Enterprise Self-RAG Agent with LangGraph & Hybrid Search, QLoRA Domain Fine-Tuning + vLLM, Full MLOps Platform with Feast.
• ⚡ Tier 4: God Level: Pre-training a 1B Foundation LLM with PyTorch FSDP & FlashAttention-2, Autonomous Multi-Agent Software Engineer with Docker Sandbox & Anthropic Model Context Protocol (MCP), Latent Diffusion Model from scratch, Custom C++/CUDA Tensor Engine.

4. First-Principles Formula Sheet & 2026 Tool Arsenal

• Mathematical formulas for Scaled Dot-Product Attention, RoPE, Multi-Head Attention, Adam optimizer equations, Binary Cross-Entropy, KL Divergence, and Focal Loss.
• Standard tool stack: PyTorch, vLLM, DeepSpeed, LangGraph, Model Context Protocol (MCP), Qdrant, Feast, and Evidently AI.

5. Gamified HUD & Native 8-Bit Web Audio

• Live level progression from LVL 01: Novice Hacker to LVL 10: Turing-Level Overlord.
• Native Web Audio API sound synthesizer with zero external audio assets (muteable with instant toggle).
• Custom retro-arcade cursor with responsive target crosshair states.
• Dual themes: Retro Arcade Light Cream and Dark Cyber Synthwave.

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🚀 Quickstart & Local Setup

Running the project requires zero build tools or complex package installations—it is built with pure, high-performance web standards (HTML5, CSS3, ES6+ JavaScript).

# 1. Clone repository
git clone https://github.com/CoderOggy78/tensorarcade.git
cd tensorarcade

# 2. Run local HTTP server
python3 -m http.server 8080

# 3. Open in browser
open http://localhost:8080

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📂 Project Structure

tensorarcade/
├── index.html                 # Main web application entry point
├── README.md                  # Project documentation
├── .gitignore                 # Git ignore rules
├── css/
│   ├── design-system.css      # Neo-Brutalist tokens, typography, colors, borders
│   └── components.css         # Navbar, HUD, stage cards, project vault, modals, cursor
└── js/
    ├── audio.js               # Web Audio API 8-bit sound synthesizer
    ├── app.js                 # State, filters, search, custom cursor, modal controller
    └── data/
        ├── roadmap-nodes.js   # 11-Stage Roadmap tracks & submodules
        ├── resources.js       # 120+ Curated learning resources database
        ├── projects.js        # 14 Tiered portfolio project blueprints
        ├── cheatsheets.js     # First-principles math formulas & 2026 tool stack
        └── interview-prep.js  # FAANG ML system design framework & mock drills

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📜 License

Distributed under the MIT License. Open-access educational resource for all learners and developers worldwide.