Data science revealed : with feature engineering, data visualization, pipeline development, and hyperparameter tuning

Data science revealed with feature engineering, data visualization, pipeline development, and hyperparameter tuning

Get insight into data science techniques such as data engineering and visualization, statistical modeling, machine learning, and deep learning. This book teaches you how to select variables, optimize hyper parameters, develop pipelines, and train, test, and validate machine and deep learning models....

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Bibliographic Details
Other Authors: Nokeri, Tshepo Chris, author (author)
Format: eBook
Language:Inglés
Published: California : Apress L. P. [2021]
Edition:1st ed. 2021.
Subjects:
Data mining.
See on Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009631751606719
Table of Contents:
  • Chapter 1: An Introduction to Simple Linear Regression Analysis
  • Chapter 2: Advanced Parametric Methods
  • Chapter 3: Time Series Analysis
  • Chapter 4: High-Quality Time Series Analysis
  • Chapter 5: Logistic Regression Analysis
  • Chapter 6: Dimension Reduction and Multivariate Analysis Using Linear Discriminant Analysis
  • Chapter 7: Finding Hyperplanes Using Support Vectors
  • Chapter 8: Classification Using Decision Trees
  • Chapter 9: Back to the Classics
  • Chapter 10: Cluster Analysis
  • Chapter 11: Survival Analysis
  • Chapter 12: Neural Networks
  • Chapter 13: Machine Learning Using H2O.

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