Book

R Machine Learning Projects

The purpose of the book is to help a machine learning practitioner gets hands-on experience in working with real-world data and apply modern machine learning algorithms. You will learn to implement each algorithm to a specific industry problem. It covers projects involving both supervised as well as unsupervised learning approaches.

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Difficulty Level
Intermediate
Completion Time
11h8m approx.
Language
English
Certification
Not available

About Course

Book Content

chapters 11h8m total length

1. Exploring the Machine Learning Landscape
2. Predicting Employees Attrition using Ensemble models
3. Implementing a Jokes Recommendation Engine
4. Sentiment Analysis of Amazon Reviews with NLP
5. Customer Segmentation Using Wholesale Data
6. Image Recognition using Deep Neural Network
7. Credit Card Fraud Detection Using Autoencoders
8. Automatic Prose Generation with Recurrent Neural Networks
9. Winning the Casino Slot Machine with Reinforcement Learning
10. Appendix

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