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How to Start Using Flowise
Run Flowise, drag a tiny LLM/agent flow, and learn visual agent building for after-work beginners.
Academy notes
Articles and updates from SoloQuant Academy.
Tag: python
Run Flowise, drag a tiny LLM/agent flow, and learn visual agent building for after-work beginners.
Install or open n8n, build one AI Agent workflow for reports or alerts, and automate beyond chat after work.
Spin up Dify, build one low-code LLM app or agent, and ship an internal tool after work without heavy infra.
Install OpenClaw from openclaw.ai, connect one chat channel, and run a personal coding/agent harness you can message after work.
Install Claude Desktop, enable one connector/MCP server, and call a local tool from chat—no CLI required tonight.
Install FastMCP from gofastmcp.com, expose one Python function as an MCP tool, and run it locally after work.
Learn what MCP is, why coding agents need it, and take one official quickstart step tonight—USB-C for AI tools.
Hoseinzade & Haratizadeh (2018) propose CNNPred—CNN models for stock market prediction from crafted feature representations. Plain-language intro. Not investment advice.
Harvey, Liu & Zhu (2016) raise the multiple-testing bar for factors—often summarised as needing much higher t-stats than 1.96. Plain-language intro. Not investment advice.
Asness, Moskowitz & Pedersen (2013) show value and momentum premia—and their negative correlation—across markets and asset classes. Plain-language intro. Not investment advice.
Moskowitz, Ooi & Pedersen (2012) document time-series momentum: trend-follow each asset’s own past returns. Plain-language intro. Not investment advice.
Giglio & Xiu (2021) provide a multiple-testing toolkit for thousands of alphas—guardrails against fake discovery. Plain-language intro. Not investment advice.