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Practical Machine Learning In R
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Guides Professionals And Students Through The Rapidly Growing Field Of Machine Learning With Handson Examples In The Popular R Programming Languagemachine Learninga Branch Of Artificial Intelligence (Ai) Which Enables Computers To Improve Their Results And Learn New Approaches Without Explicit Instructionsallows Organizations To Reveal Patterns In Their Data And Incorporate Predictive Analytics Into Their Decisionmaking Process. Practical Machine Learning In R Provides A Handson Approach To Solving Business Problems With Intelligent, Selflearning Computer Algorithms.Bestselling Author And Data Analytics Experts Fred Nwanganga And Mike Chapple Explain What Machine Learning Is, Demonstrate Its Organizational Benefits, And Provide Handson Examples Created In The R Programming Language. A Perfect Guide For Professional Selftaught Learners Or Students In An Introductory Machine Learning Course, This Readerfriendly Book Illustrates The Numerous Realworld 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 Xgboostpractical Machine Learning In R Is A Musthave 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.
⚠️ WARNING (California Proposition 65):
This product may contain chemicals known to the State of California to cause cancer, birth defects, or other reproductive harm.
For more information, please visit www.P65Warnings.ca.gov.
- Q: What is the page count of 'Practical Machine Learning in R'? A: The book contains four hundred sixty-four pages. This extensive page count provides a thorough exploration of machine learning concepts and applications.
- Q: What are the dimensions of 'Practical Machine Learning in R'? A: The book measures seven point three inches in length, zero point eight inches in width, and nine point one inches in height. These dimensions make it a convenient size for reading and reference.
- Q: What type of binding does 'Practical Machine Learning in R' have? A: The book is published in paperback binding. This format is lightweight and flexible, making it easy to carry and read.
- Q: Who are the authors of 'Practical Machine Learning in R'? A: The authors are Fred Nwanganga and Mike Chapple. Both are recognized experts in data analytics and machine learning.
- Q: What is the primary focus of 'Practical Machine Learning in R'? A: The book focuses on machine learning using the R programming language. It provides practical examples and techniques for solving business problems.
- Q: Is 'Practical Machine Learning in R' suitable for beginners? A: Yes, the book is suitable for beginners. It is designed for self-taught learners and students new to machine learning.
- Q: How can I use the techniques from 'Practical Machine Learning in R'? A: You can apply the techniques by following the hands-on examples provided in the book. These examples guide you through real-world business problems.
- Q: What skills will I learn from 'Practical Machine Learning in R'? A: You will learn skills in data wrangling, classification techniques, and performance evaluation. The book covers essential machine learning concepts in a practical manner.
- Q: Is 'Practical Machine Learning in R' appropriate for advanced users? A: Yes, advanced users can also benefit from this book. It covers complex topics like ensemble methods, which are relevant for experienced practitioners.
- Q: How should I store 'Practical Machine Learning in R'? A: Store the book in a cool, dry place away from direct sunlight. This will help preserve its condition over time.
- Q: Can I lend 'Practical Machine Learning in R' to a friend? A: Yes, you can lend the book to a friend. Just ensure they handle it carefully to avoid wear and tear.
- Q: What if 'Practical Machine Learning in R' arrives damaged? A: If the book arrives damaged, contact the seller for a return or replacement policy. Most retailers offer options for defective items.
- Q: Is there a warranty on 'Practical Machine Learning in R'? A: Typically, books do not come with a warranty. However, check with the retailer for their specific return policies.
- Q: What kind of support is available for 'Practical Machine Learning in R'? A: Support is usually available through the publisher’s website or customer service. They may provide additional resources or answers to your queries.
- Q: Does 'Practical Machine Learning in R' cover current trends in machine learning? A: Yes, the book discusses current trends and techniques used in the field of machine learning. It is up-to-date with industry practices.