Title: An Introduction to Statistical Learning: with Applications in Python Author(s) Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani Publisher: Springer; 1st ed. 2023 edition (September 8, 2023);
scMODAL: a general deep learning framework for comprehensive single-cell multi-omics data alignment with feature links Single-cell multi-omics integration is challenged by varied feature relationships and modality-specific limitations. Here, the authors present scMODAL, a deep learning framework that ...
exploratory data analysis, and unsupervised learning. The second part on inferential data analysis covers linear and logistic regression and regularization. The last part studies machine learning with a focus on support-vector machines and deep learning. Each chapter is based on a dataset...
Python, giving tutorials from the ground up, and progressing with more detailed sessions that implement the techniques in each chatper. We also offer the separate and original version of this course called Statistical Learning with R – the chapter lectures are the same, but the lab lectures ...
斯坦福大学《统计学习导论2023Python版|An Introduction to Statistical Learning with Python》中英字幕 3.7万播放 [001]1.1 Opening Remarks.zh_en 18:19 [002]8 Years Later (Second Edition of the Course).zh_en 02:19 [003].Third Edition of the Course I 2023.zh_en 01:49 [004]1.2 Examples and ...
Each edition contains a lab at the end of each chapter, which demonstrates the chapter’s concepts in either R or Python. The chapters cover the following topics: What is statistical learning? Regression Classification Resampling methods Linear model selection and regularization ...
Python相关资料 An Introduction to Statistical Learning 下载积分: 700 内容提示: Springer Texts in StatisticsSeries Editors:G. CasellaS. FienbergI. OlkinFor further volumes:http://www.springer.com/series/417 文档格式:PDF | 页数:440 | 浏览次数:78 | 上传日期:2022-07-07 18:21:39 | 文档星级:...
It is primarily aimed at beginners who want a gentle, succinct guide to jumpstart their journey into practical machine learning and its applications in medicine. Thus, it is by no means a comprehensive guide on machine learning or Python. Rather, my hope is to present basic concepts in a ...
Title: An Introduction to Statistical Learning: with Applications in R, 2nd Edition Author(s) Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani Publisher: Springer; 2nd ed. (2021); eBook (Corrected Edition, June 21, 2023) Hardcover: 622 pages eBook: PDF (615 pages) Language:...
Module 6 of Math 569: Statistical Learning delves into model evaluation and model selection via hyperparameter choice. It begins with an understanding of Bias-Variance Decomposition, highlighting the trade-off between model simplicity and accuracy. The module then explores model complexity, offering stra...