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Derivatives Analytics with Python: Data Analysis, Models, Simulation, Calibration and Hedging (The Wiley Finance Series)
Derivatives Analytics with Python: Data Analysis, Models, Simulation, Calibration and Hedging (The Wiley Finance Series)

Supercharge options analytics and hedging using the power ofPython

Derivatives Analytics with Python shows you how toimplement market-consistent valuation and hedging approaches usingadvanced financial models, efficient numerical techniques, and thepowerful capabilities of the Python programming language. Thisunique...

Introduction to Computational Models with Python (Chapman & Hall/CRC Computational Science)
Introduction to Computational Models with Python (Chapman & Hall/CRC Computational Science)

Introduction to Computational Models with Python explains how to implement computational models using the flexible and easy-to-use Python programming language. The book uses the Python programming language interpreter and several packages from the huge Python Library that improve the performance of numerical computing, such...

Python High Performance Programming
Python High Performance Programming

If you have at least a basic knowledge of Python, this book will help you maximize the performance of your code and applications. Easy to follow tutorials will make you a hard act to follow in Python programming.

Overview

  • Identify the bottlenecks in your applications and solve them using the best...
Advanced Quantitative Finance with C++
Advanced Quantitative Finance with C++

Create and implement mathematical models in C++ using Quantitative Finance

About This Book

  • Describes the key mathematical models used for price equity, currency, interest rates, and credit derivatives
  • The complex models are explained step-by-step along with a flow chart of every...
An Introduction to Numerical Analysis for Electrical and Computer Engineers
An Introduction to Numerical Analysis for Electrical and Computer Engineers
An engineer’s guide to numerical analysis

To properly function in today’s work environment, engineers require a working familiarity with numerical analysis. This book provides that necessary background, striking a balance between analytical rigor and an applied approach focusing on methods particular to the solving of engineering...

Practical Data Analysis
Practical Data Analysis

Transform, model, and visualize your data through hands-on projects, developed in open source tools

Overview

  • Explore how to analyze your data in various innovative ways and turn them into insight
  • Learn to use the D3.js visualization tool for exploratory data analysis
  • ...
Elementary Mechanics Using Python: A Modern Course Combining Analytical and Numerical Techniques (Undergraduate Lecture Notes in Physics)
Elementary Mechanics Using Python: A Modern Course Combining Analytical and Numerical Techniques (Undergraduate Lecture Notes in Physics)

This book – specifically developed as a novel textbook on elementary classical mechanics – shows how analytical and numerical methods can be seamlessly integrated to solve physics problems. This approach allows students to solve more advanced and applied problems at an earlier stage and equips them to deal with real-world examples...

Python Data Analysis Cookbook
Python Data Analysis Cookbook

Key Features

  • Analyze Big Data sets, create attractive visualizations, and manipulate and process various data types
  • Packed with rich recipes to help you learn and explore amazing algorithms for statistics and machine learning
  • Authored by Ivan Idris, expert in python programming and proud...
The Linear Algebra a Beginning Graduate Student Ought to Know
The Linear Algebra a Beginning Graduate Student Ought to Know

Linear algebra is a living, active branch of mathematics which is central to almost all other areas of mathematics, both pure and applied, as well as to computer science, to the physical, biological, and social sciences, and to engineering. It encompasses an extensive corpus of theoretical results as well as a large and rapidly-growing body...

Advanced Number Theory
Advanced Number Theory
Eminent mathematician/teacher approaches algebraic number theory from historical standpoint. Demonstrates how concepts, definitions, theories have evolved during last 2 centuries. Abounds with numerical examples, over 200 problems, many concrete, specific theorems. Includes numerous graphs and tables.

The prerequisites for this book
...
Practical Data Science Cookbook - Second Edition
Practical Data Science Cookbook - Second Edition

Over 85 recipes to help you complete real-world data science projects in R and Python

About This Book

  • Tackle every step in the data science pipeline and use it to acquire, clean, analyze, and visualize your data
  • Get beyond the theory and implement real-world projects in data science using...
Matrix Algebra: Theory, Computations, and Applications in Statistics (Springer Texts in Statistics)
Matrix Algebra: Theory, Computations, and Applications in Statistics (Springer Texts in Statistics)

Matrix algebra is one of the most important areas of mathematics for data analysis and for statistical theory. This much-needed work presents the relevant aspects of the theory of matrix algebra for applications in statistics. It moves on to consider the various types of matrices encountered in statistics, such as projection matrices and...

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