Data Mining For Mathematicians

​​​​Describing novel mathematical concepts for recommendation engines, Realtime Data Mining: Self-Learning Techniques for Recommendation Engines features a sound mathematical framework unifying approaches based on control and learning theories, tensor factorization, and hierarchical methods.

​​​​Describing novel mathematical concepts for recommendation engines, Realtime Data Mining: Self-Learning Techniques for Recommendation Engines features a sound mathematical framework unifying approaches based on control and learning theories, tensor factorization, and hierarchical methods.

R, Python data science with R programming, handle with data, manipulate data and outcomes with R (programming language)

R, Python data science with R programming, handle with data, manipulate data and outcomes with R (programming language)

Python Data Science A-Z, Data Science with Machine Learning A-Z, Deep Learning A-Z, Pandas, Numpy and R Statistics

This unique book presents innovative and state-of-the-art computational models for determining the optimal truck–loader selection and allocation strategy for use in large and complex mining operations. The authors provide comprehensive information on the methodology that has been developed over the past 50 years, from the early ad hoc spreadsheet approaches to today’s highly sophisticated and accurate mathematical-based computational models.

Learn data science with R programming and Python. Use NumPy, Pandas to manipulate the data and produce outcomes | R