Mathematical Foundations for Data Analysis
This textbook, suitable for an early undergraduate up to a graduate course, provides an overview of many basic principles and techniques needed for modern data analysis. In particular, this book was designed and written as preparation for students planning to take rigorous Machine Learning and Data...
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| Format: | eBook |
| Language: | English |
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Cham
Springer International Publishing
2021, 2021
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| Edition: | 1st ed. 2021 |
| Series: | Springer Series in the Data Sciences
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| Subjects: | |
| Online Access: | |
| Collection: | Springer eBooks 2005- - Collection details see MPG.ReNa |
Table of Contents:
- Probability review
- Convergence and sampling
- Linear algebra review
- Distances and nearest neighbors
- Linear Regression
- Gradient descent
- Dimensionality reduction
- Clustering
- Classification
- Graph structured data
- Big data and sketching