A Handbook Of Mathematical Models With Python

DOWNLOAD

Download A Handbook Of Mathematical Models With Python PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get A Handbook Of Mathematical Models With Python book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page

A Handbook Of Mathematical Models With Python

DOWNLOAD
Author : Dr. Ranja Sarkar
language : en
Publisher: Packt Publishing Ltd
Release Date : 2023-08-30

A Handbook Of Mathematical Models With Python written by Dr. Ranja Sarkar and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-08-30 with Computers categories.

Master the art of mathematical modeling through practical examples, use cases, and machine learning techniques Key Features Gain a profound understanding of various mathematical models that can be integrated with machine learning Learn how to implement optimization algorithms to tune machine learning models Build optimal solutions for practical use cases Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionMathematical modeling is the art of transforming a business problem into a well-defined mathematical formulation. Its emphasis on interpretability is particularly crucial when deploying a model to support high-stake decisions in sensitive sectors like pharmaceuticals and healthcare. Through this book, you’ll gain a firm grasp of the foundational mathematics underpinning various machine learning algorithms. Equipped with this knowledge, you can modify algorithms to suit your business problem. Starting with the basic theory and concepts of mathematical modeling, you’ll explore an array of mathematical tools that will empower you to extract insights and understand the data better, which in turn will aid in making optimal, data-driven decisions. The book allows you to explore mathematical optimization and its wide range of applications, and concludes by highlighting the synergetic value derived from blending mathematical models with machine learning. Ultimately, you’ll be able to apply everything you’ve learned to choose the most fitting methodologies for the business problems you encounter.What you will learn Understand core concepts of mathematical models and their relevance in solving problems Explore various approaches to modeling and learning using Python Work with tested mathematical tools to gather meaningful insights Blend mathematical modeling with machine learning to find optimal solutions to business problems Optimize ML models built with business data, apply them to understand their impact on the business, and address critical questions Apply mathematical optimization for data-scarce problems where the objective and constraints are known Who this book is forIf you are a budding data scientist seeking to augment your journey with mathematics, this book is for you. Researchers and R&D scientists will also be able to harness the concepts covered to their full potential. To make the best use of this book, a background in linear algebra, differential equations, basics of statistics, data types, data structures, and numerical algorithms will be useful.

Handbook Of Mathematical Models And Algorithms In Computer Vision And Imaging

DOWNLOAD
Author : Ke Chen
language : en
Publisher: Springer Nature
Release Date : 2023-02-24

Handbook Of Mathematical Models And Algorithms In Computer Vision And Imaging written by Ke Chen and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-02-24 with Mathematics categories.

This handbook gathers together the state of the art on mathematical models and algorithms for imaging and vision. Its emphasis lies on rigorous mathematical methods, which represent the optimal solutions to a class of imaging and vision problems, and on effective algorithms, which are necessary for the methods to be translated to practical use in various applications. Viewing discrete images as data sampled from functional surfaces enables the use of advanced tools from calculus, functions and calculus of variations, and nonlinear optimization, and provides the basis of high-resolution imaging through geometry and variational models. Besides, optimization naturally connects traditional model-driven approaches to the emerging data-driven approaches of machine and deep learning. No other framework can provide comparable accuracy and precision to imaging and vision. Written by leading researchers in imaging and vision, the chapters in this handbook all start with gentle introductions, which make this work accessible to graduate students. For newcomers to the field, the book provides a comprehensive and fast-track introduction to the content, to save time and get on with tackling new and emerging challenges. For researchers, exposure to the state of the art of research works leads to an overall view of the entire field so as to guide new research directions and avoid pitfalls in moving the field forward and looking into the next decades of imaging and information services. This work can greatly benefit graduate students, researchers, and practitioners in imaging and vision; applied mathematicians; medical imagers; engineers; and computer scientists.

Machine Learning With Lightgbm And Python

DOWNLOAD
Author : Andrich van Wyk
language : en
Publisher: Packt Publishing Ltd
Release Date : 2023-09-29

Machine Learning With Lightgbm And Python written by Andrich van Wyk and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-09-29 with Computers categories.

Take your software to the next level and solve real-world data science problems by building production-ready machine learning solutions using LightGBM and Python Key Features Get started with LightGBM, a powerful gradient-boosting library for building ML solutions Apply data science processes to real-world problems through case studies Elevate your software by building machine learning solutions on scalable platforms Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionMachine Learning with LightGBM and Python is a comprehensive guide to learning the basics of machine learning and progressing to building scalable machine learning systems that are ready for release. This book will get you acquainted with the high-performance gradient-boosting LightGBM framework and show you how it can be used to solve various machine-learning problems to produce highly accurate, robust, and predictive solutions. Starting with simple machine learning models in scikit-learn, you’ll explore the intricacies of gradient boosting machines and LightGBM. You’ll be guided through various case studies to better understand the data science processes and learn how to practically apply your skills to real-world problems. As you progress, you’ll elevate your software engineering skills by learning how to build and integrate scalable machine-learning pipelines to process data, train models, and deploy them to serve secure APIs using Python tools such as FastAPI. By the end of this book, you’ll be well equipped to use various -of-the-art tools that will help you build production-ready systems, including FLAML for AutoML, PostgresML for operating ML pipelines using Postgres, high-performance distributed training and serving via Dask, and creating and running models in the Cloud with AWS Sagemaker.What you will learn Get an overview of ML and working with data and models in Python using scikit-learn Explore decision trees, ensemble learning, gradient boosting, DART, and GOSS Master LightGBM and apply it to classification and regression problems Tune and train your models using AutoML with FLAML and Optuna Build ML pipelines in Python to train and deploy models with secure and performant APIs Scale your solutions to production readiness with AWS Sagemaker, PostgresML, and Dask Who this book is forThis book is for software engineers aspiring to be better machine learning engineers and data scientists unfamiliar with LightGBM, looking to gain in-depth knowledge of its libraries. Basic to intermediate Python programming knowledge is required to get started with the book. The book is also an excellent source for ML veterans, with a strong focus on ML engineering with up-to-date and thorough coverage of platforms such as AWS Sagemaker, PostgresML, and Dask.

Handbook Of Research On Data Driven Mathematical Modeling In Smart Cities

DOWNLOAD
Author : Pramanik, Sabyasachi
language : en
Publisher: IGI Global
Release Date : 2023-02-17

Handbook Of Research On Data Driven Mathematical Modeling In Smart Cities written by Pramanik, Sabyasachi and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-02-17 with Mathematics categories.

A smart city utilizes ICT technologies to improve the working effectiveness, share various data with the citizens, and enhance political assistance and societal wellbeing. The fundamental needs of a smart and sustainable city are utilizing smart technology for enhancing municipal activities, expanding monetary development, and improving citizens’ standards of living. The Handbook of Research on Data-Driven Mathematical Modeling in Smart Cities discusses new mathematical models in smart and sustainable cities using big data, visualization tools in mathematical modeling, machine learning-based mathematical modeling, and more. It further delves into privacy and ethics in data analysis. Covering topics such as deep learning, optimization-based data science, and smart city automation, this premier reference source is an excellent resource for mathematicians, statisticians, computer scientists, civil engineers, government officials, students and educators of higher education, librarians, researchers, and academicians.

Mathematical Modeling And Computation In Finance With Exercises And Python And Matlab Computer Codes

DOWNLOAD
Author : Cornelis W Oosterlee
language : en
Publisher: World Scientific
Release Date : 2019-10-29

Mathematical Modeling And Computation In Finance With Exercises And Python And Matlab Computer Codes written by Cornelis W Oosterlee and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-29 with Business & Economics categories.

This book discusses the interplay of stochastics (applied probability theory) and numerical analysis in the field of quantitative finance. The stochastic models, numerical valuation techniques, computational aspects, financial products, and risk management applications presented will enable readers to progress in the challenging field of computational finance.When the behavior of financial market participants changes, the corresponding stochastic mathematical models describing the prices may also change. Financial regulation may play a role in such changes too. The book thus presents several models for stock prices, interest rates as well as foreign-exchange rates, with increasing complexity across the chapters. As is said in the industry, 'do not fall in love with your favorite model.' The book covers equity models before moving to short-rate and other interest rate models. We cast these models for interest rate into the Heath-Jarrow-Morton framework, show relations between the different models, and explain a few interest rate products and their pricing.The chapters are accompanied by exercises. Students can access solutions to selected exercises, while complete solutions are made available to instructors. The MATLAB and Python computer codes used for most tables and figures in the book are made available for both print and e-book users. This book will be useful for people working in the financial industry, for those aiming to work there one day, and for anyone interested in quantitative finance. The topics that are discussed are relevant for MSc and PhD students, academic researchers, and for quants in the financial industry.

Practical Python Ai Projects

DOWNLOAD
Author : Serge Kruk
language : en
Publisher: Apress
Release Date : 2018-02-26

Practical Python Ai Projects written by Serge Kruk and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-02-26 with Computers categories.

Discover the art and science of solving artificial intelligence problems with Python using optimization modeling. This book covers the practical creation and analysis of mathematical algebraic models such as linear continuous models, non-obviously linear continuous models,and pure linear integer models. Rather than focus on theory, Practical Python AI Projects, the product of the author's decades of industry teaching and consulting, stresses the model creation aspect; contrasting alternate approaches and practical variations. Each model is explained thoroughly and written to be executed. The source code from all examples in the book is available, written in Python using Google OR-Tools. It also includes a random problem generator, useful for industry application or study. What You Will Learn Build basic Python-based artificial intelligence (AI) applications Work withmathematical optimization methods and the Google OR-Tools (Optimization Tools) suite Create several types of projects using Python and Google OR-Tools Who This Book Is For Developers and students who already have prior experience in Python coding. Some prior mathematical experience or comfort level may be helpful as well.

A Handbook Of Artificial Intelligence In Drug Delivery

DOWNLOAD
Author : Anil K. Philip
language : en
Publisher: Academic Press
Release Date : 2023-03-27

A Handbook Of Artificial Intelligence In Drug Delivery written by Anil K. Philip and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-03-27 with Computers categories.

A Handbook of Artificial Intelligence in Drug Delivery explores the use of Artificial Intelligence (AI) in drug delivery strategies. The book covers pharmaceutical AI and drug discovery challenges, Artificial Intelligence tools for drug research, AI enabled intelligent drug delivery systems and next generation novel therapeutics, broad utility of AI for designing novel micro/nanosystems for drug delivery, AI driven personalized medicine and Gene therapy, 3D Organ printing and tissue engineering, Advanced nanosystems based on AI principles (nanorobots, nanomachines), opportunities and challenges using artificial intelligence in ADME/Tox in drug development, commercialization and regulatory perspectives, ethics in AI, and more. This book will be useful to academic and industrial researchers interested in drug delivery, chemical biology, computational chemistry, medicinal chemistry and bioinformatics. The massive time and costs investments in drug research and development necessitate application of more innovative techniques and smart strategies. - Focuses on the use of Artificial Intelligence in drug delivery strategies and future impacts - Provides insights into how artificial intelligence can be effectively used for the development of advanced drug delivery systems - Written by experts in the field of advanced drug delivery systems and digital health

Python Data Science Handbook

DOWNLOAD
Author : Jake VanderPlas
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2016-11-21

Python Data Science Handbook written by Jake VanderPlas and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-11-21 with Computers categories.

For many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all—IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools. Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the must-have reference for scientific computing in Python. With this handbook, you’ll learn how to use: IPython and Jupyter: provide computational environments for data scientists using Python NumPy: includes the ndarray for efficient storage and manipulation of dense data arrays in Python Pandas: features the DataFrame for efficient storage and manipulation of labeled/columnar data in Python Matplotlib: includes capabilities for a flexible range of data visualizations in Python Scikit-Learn: for efficient and clean Python implementations of the most important and established machine learning algorithms

Mathematical Modeling And Simulation

DOWNLOAD
Author : Kai Velten
language : en
Publisher: John Wiley & Sons
Release Date : 2009-06-01

Mathematical Modeling And Simulation written by Kai Velten and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-06-01 with Science categories.

This concise and clear introduction to the topic requires only basic knowledge of calculus and linear algebra - all other concepts and ideas are developed in the course of the book. Lucidly written so as to appeal to undergraduates and practitioners alike, it enables readers to set up simple mathematical models on their own and to interpret their results and those of others critically. To achieve this, many examples have been chosen from various fields, such as biology, ecology, economics, medicine, agricultural, chemical, electrical, mechanical and process engineering, which are subsequently discussed in detail. Based on the author`s modeling and simulation experience in science and engineering and as a consultant, the book answers such basic questions as: What is a mathematical model? What types of models do exist? Which model is appropriate for a particular problem? What are simulation, parameter estimation, and validation? The book relies exclusively upon open-source software which is available to everybody free of charge. The entire book software - including 3D CFD and structural mechanics simulation software - can be used based on a free CAELinux-Live-DVD that is available in the Internet (works on most machines and operating systems).

Mathematical Models Of Plant Herbivore Interactions

DOWNLOAD
Author : Zhilan Feng
language : en
Publisher: CRC Press
Release Date : 2017-09-07

Mathematical Models Of Plant Herbivore Interactions written by Zhilan Feng and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-09-07 with Nature categories.

Mathematical Models of Plant-Herbivore Interactions addresses mathematical models in the study of practical questions in ecology, particularly factors that affect herbivory, including plant defense, herbivore natural enemies, and adaptive herbivory, as well as the effects of these on plant community dynamics. The result of extensive research on the use of mathematical modeling to investigate the effects of plant defenses on plant-herbivore dynamics, this book describes a toxin-determined functional response model (TDFRM) that helps explains field observations of these interactions. This book is intended for graduate students and researchers interested in mathematical biology and ecology.