Su	Mo	Tu	We	Th	Fr	Sa
31	1	2	3	4	5	6
7	8	9	10	11	12	13
14	15	16	17	18	19	20
21	22	23	24	25	26	27
28	29	30	1	2	3	4

Attention❗ To save your time, in order to download anything on this site, you must be registered 👉 HERE. If you do not have a registration yet, it is better to do it right away. ✌

( • )( • ) ( ͡⚆ ͜ʖ ͡⚆ ) (‿ˠ‿)

SpicyMags.xyz

Building Embedded System Firmware with Example Code

Posted By: eBookRat

Date: 1 Apr 2024 19:03:29

Firmware System Firmware Embedded System Firmware Robust Robust Firmware

Details

Feature-Driven Development

Posted By: eBookRat

Date: 20 Mar 2024 14:50:13

FDD Feature-Driven Development Driven Development Feature-Driven Robust Robust Software

Details

Creating Dynamic, Robust, and Scalable Applications with Python 3.11.4

Posted By: eBookRat

Date: 12 Mar 2024 09:27:36

Creating Dynamic Robust Scalable Applications Python Programming Object-Oriented Programming Object Oriented Programming OOP Oriented Programming

Details

Fragile Intelligence

Posted By: eBookRat

Date: 9 Mar 2024 18:59:13

Robust Computer Vision Robust Machine Learning Models Machine Learning Models Machine Learning

Details

"Bayesian Inference: Recent Trends" ed. by İhsan Bucak

Posted By: exLib

Date: 31 Jan 2024 23:59:42

"Bayesian Inference: Recent Trends" ed. by İhsan Bucak
ITexLi | 2024 | ISBN: 1837693552 9781837693559 1837693560 9781837693566 1837693579 9781837693573 | 78 pages | PDF | 6 MB

This book is an invaluable resource for anyone interested in the intersection of statistics, machine learning, and data science. It offers a unique perspective on Bayesian inference, revealing its potential to provide robust solutions in an increasingly data-driven world. The book is your gateway to understanding and leveraging the power of Bayesian methods in the ever-evolving landscape of data analysis.

Science Mathematics Probability Inverse Problems Statistical analysis Physics Computer Engineering Statistics Measurements Bayesian Methods Bayesian Inference Robust Data science AI Machine learning Causality analysis Finance Construction Education

Details

"Bayesian Inference: Recent Advantages" ed. by Niansheng Tang

Posted By: exLib

Date: 31 Jan 2023 23:59:50

"Bayesian Inference: Recent Advantages" ed. by Niansheng Tang
ITexLi | 2022 | ISBN: 1803560452 9781803560458 1803560444 9781803560441 1803560460 9781803560465 | 109 pages | PDF | 8 MB

This book introduces recent developments in Bayesian inference, and covers a variety of topics including robust Bayesian estimation, solving inverse problems via Bayesian theories, hierarchical Bayesian inference, and its applications for scattering experiments. The book will stimulate more extensive research on Bayesian fronts to include theories, methods, computational algorithms and applications in various fields such as data science, AI, machine learning, and causality analysis.

Science Mathematics Probability Inverse Problems Statistical analysis Physics Computer Engineering Statistics Measurements Bayesian Methods Bayesian Inference Robust Data science AI Machine learning

Details

Having the Mind of Christ: Eight Axioms to Cultivate a Robust Faith

Posted By: arundhati

Date: 16 Dec 2022 00:13:51

Christian Living Robust

Details

Introduction to Robust and Quasi-Robust Statistical Methods

Posted By: AvaxGenius

Date: 26 Jun 2022 18:51:58

Introduction to Robust and Quasi-Robust Statistical Methods by William J. J. Rey
English | PDF | 1983 | 247 Pages | ISBN : 3540128662 | 16.9 MB

The term "robustness" does not lend itself to a clear-cut statistical definition. It seems to have been introduced by G. E. P. Box in 1953 to cover a rather vague concept described in the following way by Kendall and Buckland (1981). Their dictionary states:

Science Robust Statistical Methods Probability Theory Applications of Mathematics Mathematics

Details

Adaptive Critic Control with Robust Stabilization for Uncertain Nonlinear Systems (Repost)

Posted By: AvaxGenius

Date: 28 Apr 2021 02:02:02

Adaptive Critic Control with Robust Stabilization for Uncertain Nonlinear Systems (Repost)

This book reports on the latest advances in adaptive critic control with robust stabilization for uncertain nonlinear systems. Covering the core theory, novel methods, and a number of typical industrial applications related to the robust adaptive critic control field, it develops a comprehensive framework of robust adaptive strategies, including theoretical analysis, algorithm design, simulation verification, and experimental results.

Development Nonlinear Systems Science core theory Programming Mathematics Patterns Engineering Algorithms computer science algorithm design theoretical analysis Robust Electronics Technology ePub simulation verification

Details