每个推荐都保留与其仓库、审计和安装路径的明确关联。
FinceptTerminal is a modern finance application offering advanced market analytics, investment research, and economic data tools, designed for interactive exploration and data-driven decision-making in a user-friendly environment.
This skill encodes Emil Kowalski's philosophy on UI polish, component design, animation decisions, and the invisible details that make software feel great.
A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.
Create a structured post-earnings equity research update with key metrics, estimate changes, charts, and thesis review.
A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.
Turn any technical book PDF into a Claude Code skill — ready to study, reference, and use while you work.
ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.
Superfast AI decision making and intelligent processing of multi-modal data.
A curated collection of 13 tested Claude Code agent skills for producing decks, research briefs, PRDs, articles, audits, and other finished work.
A platform-neutral analytical skill that profiles messy data, selects adaptive methods, and produces source-backed visual reports for high-stakes decisions.
A collection of reusable AI agent skills for personal operators, covering decisions, research, second-brain workflows, and more, designed for Claude Code, Codex, and Cursor.
Estimate a public companys intrinsic value through DCF, relative, and sum-of-the-parts valuation methods.
每个推荐都保留与其仓库、审计和安装路径的明确关联。
FinceptTerminal is a modern finance application offering advanced market analytics, investment research, and economic data tools, designed for interactive exploration and data-driven decision-making in a user-friendly environment.
This skill encodes Emil Kowalski's philosophy on UI polish, component design, animation decisions, and the invisible details that make software feel great.
A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.
Create a structured post-earnings equity research update with key metrics, estimate changes, charts, and thesis review.
A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.
Turn any technical book PDF into a Claude Code skill — ready to study, reference, and use while you work.
ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.
Superfast AI decision making and intelligent processing of multi-modal data.
A curated collection of 13 tested Claude Code agent skills for producing decks, research briefs, PRDs, articles, audits, and other finished work.
A platform-neutral analytical skill that profiles messy data, selects adaptive methods, and produces source-backed visual reports for high-stakes decisions.
A collection of reusable AI agent skills for personal operators, covering decisions, research, second-brain workflows, and more, designed for Claude Code, Codex, and Cursor.
Estimate a public companys intrinsic value through DCF, relative, and sum-of-the-parts valuation methods.
每个推荐都保留与其仓库、审计和安装路径的明确关联。
FinceptTerminal is a modern finance application offering advanced market analytics, investment research, and economic data tools, designed for interactive exploration and data-driven decision-making in a user-friendly environment.
This skill encodes Emil Kowalski's philosophy on UI polish, component design, animation decisions, and the invisible details that make software feel great.
A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.
Create a structured post-earnings equity research update with key metrics, estimate changes, charts, and thesis review.
A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.
Turn any technical book PDF into a Claude Code skill — ready to study, reference, and use while you work.
ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.
Superfast AI decision making and intelligent processing of multi-modal data.
A curated collection of 13 tested Claude Code agent skills for producing decks, research briefs, PRDs, articles, audits, and other finished work.
A platform-neutral analytical skill that profiles messy data, selects adaptive methods, and produces source-backed visual reports for high-stakes decisions.
A collection of reusable AI agent skills for personal operators, covering decisions, research, second-brain workflows, and more, designed for Claude Code, Codex, and Cursor.
Estimate a public companys intrinsic value through DCF, relative, and sum-of-the-parts valuation methods.
每个推荐都保留与其仓库、审计和安装路径的明确关联。
FinceptTerminal is a modern finance application offering advanced market analytics, investment research, and economic data tools, designed for interactive exploration and data-driven decision-making in a user-friendly environment.
This skill encodes Emil Kowalski's philosophy on UI polish, component design, animation decisions, and the invisible details that make software feel great.
A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.
Create a structured post-earnings equity research update with key metrics, estimate changes, charts, and thesis review.
A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.
Turn any technical book PDF into a Claude Code skill — ready to study, reference, and use while you work.
ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.
Superfast AI decision making and intelligent processing of multi-modal data.
A curated collection of 13 tested Claude Code agent skills for producing decks, research briefs, PRDs, articles, audits, and other finished work.
A platform-neutral analytical skill that profiles messy data, selects adaptive methods, and produces source-backed visual reports for high-stakes decisions.
A collection of reusable AI agent skills for personal operators, covering decisions, research, second-brain workflows, and more, designed for Claude Code, Codex, and Cursor.
Estimate a public companys intrinsic value through DCF, relative, and sum-of-the-parts valuation methods.