Department of Computing, Imperial College London. His research interests center around data-efficient and autonomous machine learning, and he has taught courses at both Imperial College London and at the African Institute for Mathematical Sciences (Rwanda). Deisenroth was Program Chair of EWRL 201.....
Other Titles in Applied Mathematics(共138册),这套丛书还有 《Metabolic Networks, Elementary Flux Modes, and Polyhedral Cones》《Introduction to Interval Analysis》《Dynamics and Bifurcation in Networks》《Machine Learning for Asset Pricing and Management》《Numerical Linear Algebra with Julia》等。 我来...
A wonderful summary of Mathematical Tricks Commonly Used in Machine Learning and Statistics with examples I just realized that when I teach ridge regression I should have used A Useful Matrix Inverse Equality for Ridge Regression GANs should be gained much attention in the stats community: Understandi...
As with the first edition, Mathematics for Finance: An Introduction to Financial Engineering combines financial motivation with mathematical style. Assuming only basic knowledge of probability and calculus, it presents three major areas of mathematical finance, namely Option pricing based on the no-arbitr...
(摘自本人博客:http://blog.zhenghui.org/2013/07/24/magic-of-math/ 或:http://en.zhenghui.org/2013/05/18/magic-of-math_CN/) 人民邮电出版社出版的《具体数学——计算机科学基础》译自经典名著 《Concrete Mathematics: A Foundation for Computer Science》。 简单地... (展开) 61 2 1回应 clk...
副标题: Discover math principles that fuel algorithms for computer science and machine learning with Python出版年: 2021-2-22页数: 330ISBN: 9781838983147豆瓣评分 目前无人评价 评价: 写笔记 写书评 加入购书单 分享到 推荐 内容简介 ··· A practical guide simplifying discrete math for curious minds ...
出版社:Basingstoke : Palgrave 副标题:K. A. Stroud; with additions by Dexter J. Booth. 5th ed. 出版年:2001 页数:1236 ISBN:9780333919392 豆瓣评分 评价人数不足 评价: 写笔记 写书评 加入购书单 分享到 推荐 内容简介· ··· This introductory mathematics course for students on science and enginee...
Gaussian Processes for Machine ... 9.0 Combinatorial Optimization 8.7 统计学习理论的本质 9.1 Pattern Recognition and Machine L... 9.5 Reinforcement Learning 8.8 Introductory Functional Analysis wit... 9.5 Elements of Information Theory 9.0 The Elements of Statistical Learnin... 9.4 ...