- Main
- Mathematics - Computational Mathematics
- Essential Math for Data Science
Essential Math for Data Science
Thomas NieldQuanto Você gostou deste livro?
Qual é a qualidade do ficheiro descarregado?
Descarregue o livro para avaliar a sua qualidade
De que qualidade são os ficheiros descarregados?
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
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
Categorias:
Ano:
2022
Edição:
1
Editora:
O'Reilly Media
Idioma:
english
Páginas:
350
ISBN 10:
1098102924
ISBN 13:
9781098102937
Arquivo:
EPUB, 7.64 MB
As suas tags:
IPFS:
CID , CID Blake2b
english, 2022
O arquivo será enviado para o email durante 1-5 minutos.
O arquivo será enviado a você através do Messenger Telegram. Pode levar de 1 a 5 minutos antes de recebê-lo.
NOTA: Verifique se você ligou a sua conta ao Telegram Bot da Z-Library.
O arquivo será enviado para sua conta do Kindle. Pode levar de 1 a 5 minutos antes de recebê-lo.
Nota: Você precisa verificar cada livro que envia para o Kindle. Verifique sua caixa de e-mail para um e-mail de confirmação do Amazon Kindle Support.
A converter para
Conversão para falhou
Benefícios do estatuto premium
- Envie para leitores eletrónicos
- Limite aumentado de download
- Converter ficheiros
- Mais resultados de pesquisa
- Outros benefícios