Home eBooks Download › linear algebra for data science in python

Linear Algebra For Data Science In Python

Download Linear Algebra For Data Science In Python PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Linear Algebra For Data Science In 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

Practical Linear Algebra For Data Science

DOWNLOAD
Author : MIKE. COHEN
language : en
Publisher: O'Reilly Media
Release Date : 2022-11-30

Practical Linear Algebra For Data Science written by MIKE. COHEN and has been published by O'Reilly Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-11-30 with Computers categories.

If you want to work in any computational or technical field, you need to understand linear algebra. As the study of matrices and operations acting upon them, linear algebra is the mathematical basis of nearly all algorithms and analyses implemented in computers. But the way it's presented in decades-old textbooks is much different from how professionals use linear algebra today to solve real-world modern applications. This practical guide from Mike X Cohen teaches the core concepts of linear algebra as implemented in Python, including how they're used in data science, machine learning, deep learning, computational simulations, and biomedical data processing applications. Armed with knowledge from this book, you'll be able to understand, implement, and adapt myriad modern analysis methods and algorithms. Ideal for practitioners and students using computer technology and algorithms, this book introduces you to: The interpretations and applications of vectors and matrices Matrix arithmetic (various multiplications and transformations) Independence, rank, and inverses Important decompositions used in applied linear algebra (including LU and QR) Eigendecomposition and singular value decomposition Applications including least-squares model fitting and principal components analysis

Practical Linear Algebra For Data Science

DOWNLOAD
Author : Mike X Cohen
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2022-09-06

Practical Linear Algebra For Data Science written by Mike X Cohen 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 2022-09-06 with Computers categories.

Linear Algebra For Data Science In Python

DOWNLOAD
Author : 365 Careers
language : en
Publisher:
Release Date : 2019

Linear Algebra For Data Science In Python written by 365 Careers and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with categories.

Know all about Linear Algebra for Data Science in Python About This Video Learn linear algebra for data science and understand the essential concepts Understand matrix, scalars, and vectors and learn how to use them In Detail Vectorizing your code is an essential skill to make your calculations faster and take advantage of the capabilities of modern machine and deep learning packages. This course will get you up and running with linear algebra fundamentals for data science in Python. In this course, you will learn about scalars, vectors, and matrices and the geometrical meaning of these objects. You will also learn how you should use linear algebra in your Python code. In addition to this, you'll be able to perform operations such as addition, subtraction and dot product. As you cover further sections, you'll focus on the different syntactical errors you can encounter while vectorizing your code. By the end of this course, you will have gained the skills you need to use linear algebra confidently in your data science projects. Downloading the example code for this course: You can download the example code files for this course on GitHub at the following link: https://github.com/PacktPublishing/Linear-Algebra-for-Data-Science-in-Python . If you require support please email: [email protected].

Linear Algebra For Data Science Machine Learning And Signal Processing

DOWNLOAD
Author : Jeffrey A. Fessler
language : en
Publisher: Cambridge University Press
Release Date : 2024-05-16

Linear Algebra For Data Science Machine Learning And Signal Processing written by Jeffrey A. Fessler and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-16 with Computers categories.

Master matrix methods via engaging data-driven applications, aided by classroom-tested quizzes, homework exercises and online Julia demos.

Practical Linear Algebra For Data Science

DOWNLOAD
Author : Mike Cohen
language : en
Publisher:
Release Date : 2022

Practical Linear Algebra For Data Science written by Mike Cohen and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022 with categories.

Data Science With Python Guide For Beginners

DOWNLOAD
Author : Mustafa Ali
language : en
Publisher: Mustafa Ali
Release Date : 2024-02-01

Data Science With Python Guide For Beginners written by Mustafa Ali and has been published by Mustafa Ali this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-01 with Computers categories.

Python's Reign in Data Science: Its intuitive syntax, robust libraries (pandas, NumPy, scikit-learn), and active community make Python the lingua franca of data analysis.

Basics Of Linear Algebra For Machine Learning

DOWNLOAD
Author : Jason Brownlee
language : en
Publisher: Machine Learning Mastery
Release Date : 2018-01-24

Basics Of Linear Algebra For Machine Learning written by Jason Brownlee and has been published by Machine Learning Mastery this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-01-24 with Computers categories.

Linear algebra is a pillar of machine learning. You cannot develop a deep understanding and application of machine learning without it. In this laser-focused Ebook, you will finally cut through the equations, Greek letters, and confusion, and discover the topics in linear algebra that you need to know. Using clear explanations, standard Python libraries, and step-by-step tutorial lessons, you will discover what linear algebra is, the importance of linear algebra to machine learning, vector, and matrix operations, matrix factorization, principal component analysis, and much more.

Linear Algebra Coding With Python

DOWNLOAD
Author : Hyun-Seok Son
language : en
Publisher: Hyun-Seok Son
Release Date : 2020-08-11

Linear Algebra Coding With Python written by Hyun-Seok Son and has been published by Hyun-Seok Son this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-11 with Art categories.

Python is one of the most popular languages for data analysis and prediction. What's more, tensorflow and torch, useful tools of recent deep learning, are fully implemented by Python. The basic form of data in these languages is an array, created by Python's important package numpy. In particular, arrays are the basis of data science because they have structures of vectors and matrices that give the meaning of direction and magnitude to each value in the data set. The matrix structure allows transformation to a simple form without losing the basic characteristics of a vast data set. These transformations are useful for efficient processing of data and for finding implicit characteristics. Linear Algebra, a field that provides a basic theory of vectors and matrices, provides many algorithms to increase the accuracy and speed of computation for analyzing data and to discover the characteristics of a data set. These algorithms are very useful for understanding the computing process of probability, statistics and the learning machine. This book introduces many basics of linear algebra using Python packages numpy, sympy, and so on. Chapters 1 and 2 introduce the creation and characteristics of vectors and matrices. Chapter 3 describes the linear system(linear combination) through the process finding the solution in a system of simultaneous equations. Vector space, a concept introduced in Chapter 4, is used to infer the collective characteristics and relationships of each vector of a linear system. Chapter 5 introduces the coordinate system to represent the linear system geometrically. Chapter 6 introduces the process of transforming while maintaining basic characteristics such as vectors and matrices. Finally, Chapter 7 describes several ways to decompose the original form into a simple form. In this process, we use a variety of Python functions.

Essential Math For Data Science

DOWNLOAD
Author : Thomas Nield
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2022-05-26

Essential Math For Data Science written by Thomas Nield 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 2022-05-26 with categories.

Master the math needed to excel in data science, machine learning, and statistics. In this book author Thomas Nield guides you through areas like calculus, probability, linear algebra, and statistics and how they apply to techniques like linear regression, logistic regression, and neural networks. Along the way you'll also gain practical insights into the state of data science and how to use those insights to maximize your career. Learn how to: Use Python code and libraries like SymPy, NumPy, and scikit-learn to explore essential mathematical concepts like calculus, linear algebra, statistics, and machine learning Understand techniques like linear regression, logistic regression, and neural networks in plain English, with minimal mathematical notation and jargon Perform descriptive statistics and hypothesis testing on a dataset to interpret p-values and statistical significance Manipulate vectors and matrices and perform matrix decomposition Integrate and build upon incremental knowledge of calculus, probability, statistics, and linear algebra, and apply it to regression models including neural networks Navigate practically through a data science career and avoid common pitfalls, assumptions, and biases while tuning your skill set to stand out in the job market

Data Science From Scratch

DOWNLOAD
Author : Steven Cooper
language : en
Publisher: Roland Bind
Release Date : 2018-08-10

Data Science From Scratch written by Steven Cooper and has been published by Roland Bind this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-08-10 with Computers categories.

★☆If you are looking to start a new career that is in high demand, then you need to continue reading!★☆ Data scientists are changing the way big data is used in different institutions. Big data is everywhere, but without the right person to interpret it, it means nothing. So where do business find these people to help change their business? You could be that person! It has become a universal truth that businesses are full of data. With the use of big data, the US healthcare could reduce their health-care spending by $300 billion to $450 billion. It can easily be seen that the value of big data lies in the analysis and processing of that data, and that's where data science comes in. ★★ Grab your copy today and learn ★★ ♦ In depth information about what data science is and why it is important. ♦ The prerequisites you will need to get started in data science. ♦ What it means to be a data scientist. ♦ The roles that hacking and coding play in data science. ♦ The different coding languages that can be used in data science. ♦ Why python is so important. ♦ How to use linear algebra and statistics. ♦ The different applications for data science. ♦ How to work with the data through munging and cleaning ♦ And much more... The use of data science adds a lot of value to businesses, and we will continue to see the need for data scientists grow. As businesses and the internet change, so will data science. This means it's important to be flexible. When data science can reduce spending costs by billions of dollars in the healthcare industry, why wait to jump in? If you want to get started in a new, ever growing, career, don't wait any longer. Scroll up and click the buy now button to get this book today!

Linear Algebra For Data Science In Python

Recent Posts