CS2 – Risk Modelling and Survival Analysis
5 个单元 · 21 个章节
免费 CS2 – Risk Modelling and Survival Analysis 学习笔记，适合 IFoA (Institute and Faculty of Actuaries) 学生。每个章节都覆盖一个重点主题，并附例题与可延伸到 thinka app 的练习提示。
Random variables and distributions for risk modelling
Time series
Stochastic processes
Survival models
Machine learning
Bias/variance trade-off and relationships with model complexity
Cross-validation to evaluate models on unseen data, and estimate hyper-parameters
Understand how regularisation can be used to reduce overfitting in highly parameterised models
The use of software to apply supervised learning techniques, to solve regression and classification problems
The use of metrics such as precision, recall, F1 score and diagnostics such as the ROC curve and confusion matrix to evaluate the performance of a binary classifier
Unsupervised learning techniques (principal component analysis, K-means clustering) to reduce data dimensionality, identify latent substructure and detect anomalies
看完笔记了？现在就用 AI 题目测一测自己。
马上练这一题