--- title: "stock-rnn vs ai-engineering-from-scratch" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/lilianweng-stock-rnn-vs-rohitg00-ai-engineering-from-scratch" tools: ["lilianweng-stock-rnn", "rohitg00-ai-engineering-from-scratch"] --- # stock-rnn vs ai-engineering-from-scratch *GraphCanon updated Sep 20, 2026* ## Verdict Pick stock-rnn if predicts stock market prices using LSTM-based RNNs with optional multi-stock embeddings; pick ai-engineering-from-scratch if ai-engineering-from-scratch is a comprehensive course that teaches AI engineering skills from foundational math to advanced AI agents and machine learning techniques, using Python and Node.js for interactive learning and. [stock-rnn](https://lilianweng.github.io/lil-log) reports 2.0k GitHub stars, 674 forks, and 23 open issues, last pushed Jul 28, 2022. [ai-engineering-from-scratch](https://aiengineeringfromscratch.com) has 55k stars, 9.6k forks, and 114 open issues, last pushed Sep 7, 2026. Figures are from public GitHub metadata via [stock-rnn's repository](https://github.com/lilianweng/stock-rnn) and [ai-engineering-from-scratch's repository](https://github.com/rohitg00/ai-engineering-from-scratch). | | [stock-rnn](/tools/lilianweng-stock-rnn.md) | [ai-engineering-from-scratch](/tools/rohitg00-ai-engineering-from-scratch.md) | | --- | --- | --- | | Tagline | Predict stock market prices using RNN model with multilayer LSTM cells. | Learn, build, and deploy AI engineering skills from scratch. | | Stars | 1,993 | 54,935 | | Forks | 674 | 9,649 | | Open issues | 23 | 114 | | Language | Python | Python | | Adopt for | Predicts stock market prices using LSTM-based RNNs with optional multi-stock embeddings. | ai-engineering-from-scratch is a comprehensive course that teaches AI engineering skills from foundational math to advanced AI agents and machine learning techniques, using Python and Node.js for interactive learning and | | Persona | - | - | | Runtime | - | - | | License | - | MIT | | Categories | Model Training | AI Agents, Computer Vision, Developer Tools, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [stock-rnn](/tools/lilianweng-stock-rnn.md) | [ai-engineering-from-scratch](/tools/rohitg00-ai-engineering-from-scratch.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Active (82%) | | Days since push | 1514d | 10d | | Open issues (now) | 23 | 114 | | Stars delta | +17 (30d) | +8.1k (30d) | | Open issues delta | -1 (30d) | +7 (30d) | | Full report | [trust report](/tools/lilianweng-stock-rnn/trust.md) | [trust report](/tools/rohitg00-ai-engineering-from-scratch/trust.md) | ## Shared compatibility - **Python**: [stock-rnn](/tools/lilianweng-stock-rnn.md) - Python runtime; [ai-engineering-from-scratch](/tools/rohitg00-ai-engineering-from-scratch.md) - Python runtime ## Decision facts: stock-rnn - **Adopt for:** Predicts stock market prices using LSTM-based RNNs with optional multi-stock embeddings. ## Decision facts: ai-engineering-from-scratch - **Adopt for:** ai-engineering-from-scratch is a comprehensive course that teaches AI engineering skills from foundational math to advanced AI agents and machine learning techniques, using Python and Node.js for interactive learning and ## Choose when ### Choose stock-rnn if… - Tags unique to stock-rnn: embeddings, lstm, rnn-tensorflow, stock-price-prediction. - Forecasting stock prices requires an approach that benefits from long-term memory in sequential data - Leaner open-issue backlog (23). ### Choose ai-engineering-from-scratch if… - Tags unique to ai-engineering-from-scratch: agents, ai-engineering, computer-vision, deep-learning. - Also covers AI Agents, Computer Vision, Developer Tools. - when you need a structured course that covers a wide range of AI engineering topics from scratch, including foundational math, deep learning, and reinforcement learning. ## When NOT to use stock-rnn - Short-term price predictions dominate the forecasting focus - Single-stock analysis suffices without incorporating multi-stock embeddings ## When NOT to use ai-engineering-from-scratch - if you are looking for a tool that focuses solely on theoretical knowledge without practical application, as this course emphasizes hands-on learning. - when you do not have access to Node.js or Python, as these are required for running the course and its interactive components. - if you prefer a more traditional learning approach without the use of terminal-based learning tools, as the course is designed for interactive terminal sessions. - when you are working with a development environment that does not support skill-capable hosts, as the course is optimized for such environments. ## Common questions ### What is the difference between stock-rnn and ai-engineering-from-scratch? stock-rnn: Predict stock market prices using RNN model with multilayer LSTM cells.. ai-engineering-from-scratch: Learn, build, and deploy AI engineering skills from scratch.. See the comparison table for live GitHub stats and shared categories. ### When should I choose stock-rnn over ai-engineering-from-scratch? Choose stock-rnn over ai-engineering-from-scratch when Tags unique to stock-rnn: embeddings, lstm, rnn-tensorflow, stock-price-prediction; Forecasting stock prices requires an approach that benefits from long-term memory in sequential data; Leaner open-issue backlog (23). ### When should I choose ai-engineering-from-scratch over stock-rnn? Choose ai-engineering-from-scratch over stock-rnn when Tags unique to ai-engineering-from-scratch: agents, ai-engineering, computer-vision, deep-learning; Also covers AI Agents, Computer Vision, Developer Tools; when you need a structured course that covers a wide range of AI engineering topics from scratch, including foundational math, deep learning, and reinforcement learning. ### When should I avoid stock-rnn? Short-term price predictions dominate the forecasting focus Single-stock analysis suffices without incorporating multi-stock embeddings ### When should I avoid ai-engineering-from-scratch? if you are looking for a tool that focuses solely on theoretical knowledge without practical application, as this course emphasizes hands-on learning. when you do not have access to Node.js or Python, as these are required for running the course and its interactive components. if you prefer a more traditional learning approach without the use of terminal-based learning tools, as the course is designed for interactive terminal sessions. when you are working with a development environment that does not support skill-capable hosts, as the course is optimized for such environments. ### Is stock-rnn or ai-engineering-from-scratch more popular on GitHub? ai-engineering-from-scratch has more GitHub stars (54,935 vs 1,993). Stars measure visibility, not whether either tool fits your constraints. ### Are stock-rnn and ai-engineering-from-scratch open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to stock-rnn or ai-engineering-from-scratch? GraphCanon lists graph-backed alternatives at [stock-rnn alternatives](/tools/lilianweng-stock-rnn/alternatives) and [ai-engineering-from-scratch alternatives](/tools/rohitg00-ai-engineering-from-scratch/alternatives) ([stock-rnn markdown twin](/tools/lilianweng-stock-rnn/alternatives.md), [ai-engineering-from-scratch markdown twin](/tools/rohitg00-ai-engineering-from-scratch/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/lilianweng-stock-rnn-vs-rohitg00-ai-engineering-from-scratch.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, stock-rnn or ai-engineering-from-scratch? stock-rnn: Dormant. ai-engineering-from-scratch: Active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for stock-rnn and ai-engineering-from-scratch? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [stock-rnn trust report](/tools/lilianweng-stock-rnn/trust); [ai-engineering-from-scratch trust report](/tools/rohitg00-ai-engineering-from-scratch/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=lilianweng-stock-rnn`](/api/graphcanon/graph?tool=lilianweng-stock-rnn) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_