Numerical Python: Scientific Computing and Data Science Applications with Numpy, SciPy and Matplotlib
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Leverage the numerical and mathematical modules in Python and its standard library as well as popular open source numerical Python packages like NumPy, SciPy, FiPy, matplotlib and more. This fully revised edition, updated with the latest details of each package and changes to Jupyter projects, demonstrates how to numerically compute solutions and mathematically model applications in big data, cloud computing, financial engineering, business management and more.
Numerical Python, Second Edition, presents many brand-new case study examples of applications in data science and statistics using Python, along with extensions to many previous examples. Each of these demonstrates the power of Python for rapid development and exploratory computing due to its simple and high-level syntax and multiple options for data analysis.
After reading this book, readers will be familiar with many computing techniques including array-based and symbolic computing, visualization and numerical file I/O, equation solving, optimization, interpolation and integration, and domain-specific computational problems, such as differential equation solving, data analysis, statistical modeling and machine learning.
What You’ll Learn
- Work with vectors and matrices using NumPy
- Plot and visualize data with Matplotlib
- Perform data analysis tasks with Pandas and SciPy
- Review statistical modeling and machine learning with statsmodels and scikit-learn
- Optimize Python code using Numba and Cython
Who This Book Is For
Developers who want to understand how to use Python and its related ecosystem for numerical computing.
17 reviews for Numerical Python: Scientific Computing and Data Science Applications with Numpy, SciPy and Matplotlib
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Bo Huang –
I noticed this book since it’s in the first edition in 2015. I purchased the second edition book and I skipped over it and found it’s really useful. I will suggest my university to open a new course, say “scientific and numerical computing with Python” and use this book as the text. The only regretful thing is there is no exercises in each chapter. Hopefully the writer will provide them and the solution online.
Idon’twantapenname! –
This is an excellent book. It has a whole bunch of great information for Data Scientists working with Python 3. I highly recommend this book.
Bjorn E –
This is a weirdly enjoyable read. It gives exactly the right amount of information at the right pace.
Mario José Suazo –
Amazing book
Saul Alfredo Puga Manjarrez –
Es un buen libro para quienes quieren implementar sus problemas y así obtener simulación numérica.
Ya debes de tener conocimientos de python para el uso de estas dos librerias para hacer simulacion numerica y uso de las herramientas para graficar.
arunabha –
Nice intro to python for beginners. I use it for my physics class.
Alessio –
Il testa tratta una molteplicità di argomenti fornendo spunti per riuscire ad integrare quanto riportato nel libro.
Come ho scritto nel titolo non è adatto a chi si avvicina per la prima volta al mondo di Python
Yalin –
If you don’t have coding experience and want to have a start, you should buy this book
Yuga Chitrapu –
It is nice book with some decent rigour.
Llama –
I recently decide to make a transition from Matlab to Python, and this book is where I get started. This book is well organized and provides a clear and systematic introduction to the fundamentals of Python for numerical computing. The examples and summary tables are very helpful. Explanations are to the point.
José Alberto Zamora Salvador –
Gran libro para aprender a programar, con ejemplos claros que ayudan a comprender cómo trabaja python
Elyasaf Aloni –
The book covers a large number of libraries, so naturally it tries to teach you only the basics of each one so you will be able more easily to explore the gory details of each library by yourself.
Overall, its great book for starters who know what there mathematical needs are and want to familiarize themselves with the popular mathematical libraries such as numpy, sympy, scipy, and the more advanced ones such as fenics, fipy etc.
4/5
Jeffrey A. –
Easily readable and complete. It has many clear examples.
Marcelo Assafin –
Livro excelente. Já está me ajudando na programação Python de códigos! Vai me acompanhar por anos em minha profissão!
Nancy –
The coding work made me cry sm but this book is really useful and provides rlly smart examples of many topics
NGS –
It is a very useful and excellent book of Numerical Python in which almost issues for applications are coped with. You will learn with this book a lot of using Python for real problems in physics, engineering, and Machine Learning. Thus, it is highly recommended.
BKN –
Good