Agent Based Modeling
Average Silhouette Width
Basic statistics
Big Data
Boston Housing Dataset
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Clustering Solution
Computer science
Convex Programs
Convolutional Layer
Data Analysis
Data Collection
Data science
Deep Learning Framework
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Fractal Dimension
Gradient Descent
Interior Point Methods
Klein Bottle
Linear algebra
Linearly Independent
LU Decomposition
Mathematicians
Metric Space
Multilayer Perceptron
PH
Pooling Layer
Primal Dual Interior Point Algorithm
QR Decomposition
Roc Curve
Simple Recurrent Neural Network
Stochastic Gradient Descent
TDA
Test Dataset
Version Control
Product details
- ISBN 9780367027056
- Weight: 940g
- Dimensions: 156 x 234mm
- Publication Date: 16 Sep 2020
- Publisher: Taylor & Francis Ltd
- Publication City/Country: GB
- Product Form: Hardback
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Mathematicians have skills that, if deepened in the right ways, would enable them to use data to answer questions important to them and others, and report those answers in compelling ways. Data science combines parts of mathematics, statistics, computer science. Gaining such power and the ability to teach has reinvigorated the careers of mathematicians. This handbook will assist mathematicians to better understand the opportunities presented by data science. As it applies to the curriculum, research, and career opportunities, data science is a fast-growing field. Contributors from both academics and industry present their views on these opportunities and how to advantage them.
Nathan Carter is a professor at Bentley University.
