Bộ sách luyện thi ETS 2023 LC&RC
199,000₫
299,000₫
Sách keo gáy,bìa mềm
Synthetic Data and Generative AI covers the
foundations of machine learning, with modern approaches to solving
complex problems and the systematic generation and use of synthetic
data. Emphasis is on scalability, automation, testing, optimizing, and
interpretability (explainable AI). For instance, regression techniques –
including logistic and Lasso – are presented as a single method,
without using advanced linear algebra. Confidence regions and prediction
intervals are built using parametric bootstrap, without statistical
models or probability distributions. Models (including generative models
and mixtures) are mostly used to create rich synthetic data to test and
benchmark various methods.
Emphasizes numerical stability and performance of algorithms (computational complexity)
Focuses
on explainable AI/interpretable machine learning, with heavy use of
synthetic data and generative models, a new trend in the field
Includes
new, easier construction of confidence regions, without statistics, a
simple alternative to the powerful, well-known XGBoost technique
Covers automation of data cleaning, favoring easier solutions when possible
Includes
chapters dedicated fully to synthetic data applications: fractal-like
terrain generation with the diamond-square algorithm, and synthetic star
clusters evolving over time and bound by gravity
Thể loại:Computers - Artificial Intelligence (AI)
Năm:2024
In lần thứ:1
Ngôn ngữ:english
Trang:856
