- Main
- Computers - Artificial Intelligence (AI)
- Essential Math for Data Science
Essential Math for Data Science
Thomas NieldMaster 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
- Checking other formats...
- Convertire a
- Sbloccare file di conversione di dimensioni maggiori di 8 MB Premium
Entro 1-5 minuti il file verrà consegnato al tuo account Telegram.
Attenzione: assicurati di aver collegato il tuo account al bot Z-Library Telegram.
Entro 1-5 minuti il file verrà consegnato al tuo dispositivo Kindle.
Nota: devi verificare ogni libro che desideri inviare al tuo Kindle. Controlla la tua casella di posta per l'e-mail di verifica da Amazon Kindle Support.
- Inviare a lettori di e-book
- Limite aumentato di download
- Converti i file
- Più risultati di ricerca
- Altri vantaggi