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Practical Machine Learning in R by Fred Nwanganga, Mike Chapple

• Practical Machine Learning in R
• Fred Nwanganga, Mike Chapple
• Page: 464
• Format: pdf, ePub, mobi, fb2
• ISBN: 9781119591511
• Publisher: Wiley

Download Practical Machine Learning in R

Downloads ebooks for free pdf Practical Machine Learning in R English version by Fred Nwanganga, Mike Chapple

Guides professionals and students through the rapidly growing field of machine learning with hands-on examples in the popular R programming language Machine learning—a branch of Artificial Intelligence (AI) which enables computers to improve their results and learn new approaches without explicit instructions—allows organizations to reveal patterns in their data and incorporate predictive analytics into their decision-making process. Practical Machine Learning in R provides a hands-on approach to solving business problems with intelligent, self-learning computer algorithms. Bestselling author and data analytics experts Fred Nwanganga and Mike Chapple explain what machine learning is, demonstrate its organizational benefits, and provide hands-on examples created in the R programming language. A perfect guide for professional self-taught learners or students in an introductory machine learning course, this reader-friendly book illustrates the numerous real-world business uses of machine learning approaches. Clear and detailed chapters cover data wrangling, R programming with the popular RStudio tool, classification and regression techniques, performance evaluation, and more. Explores data management techniques, including data collection, exploration and dimensionality reduction Covers unsupervised learning, where readers identify and summarize patterns using approaches such as apriori, eclat and clustering Describes the principles behind the Nearest Neighbor, Decision Tree and Naive Bayes classification techniques Explains how to evaluate and choose the right model, as well as how to improve model performance using ensemble methods such as Random Forest and XGBoost Practical Machine Learning in R is a must-have guide for business analysts, data scientists, and other professionals interested in leveraging the power of AI to solve business problems, as well as students and independent learners seeking to enter the field.

Practical Machine Learning with R and Python – Part 4
This article discusses classification with Support Vector Machines (SVMs), using both a Linear and a Radial basis kernel, and Decision Trees. It includes metrics  Practical Machine Learning in R - Fred Nwanganga, Mike
Practical Machine Learning in R · Explores data management techniques, including data collection, exploration and dimensionality reduction · Covers unsupervised  Final Project Report - Practical Machine Learning Course
R (in code/raw code) file in the gitHub repo in order to better understand the reasoning behind the tatics choosen. For instance and as a very simple example, the  Practical Machine Learning [Book] - O'Reilly
Fully-coded working examples using a wide range of machine learning libraries and tools, including Python, R, Julia, and Spark; Comprehensive practical  Practical Machine Learning in R - Wiley-VCH
Practical Machine Learning in R is a must-have guide for business analysts, data scientists, and other professionals interested in leveraging the power of AI to 

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