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Chapter 01 A Gentle Introduction to Machine Learning
Chapter 02 Important Elements in Machine Learning
Chapter 03 Feature Selection and Feature Engineering
Chapter 04 Linear Regression
Chapter 05 Logistic Regression
Chapter 06 Navie Bayes
Chapter 07 Support Vector Machines
Chapter 08 Decision Trees and Ensemble Learning
Chapter 09 Clustering Fundamentals
Chapter 10 Hierarchical Clustering
Chapter 11 Introduction to Recommendation Systems
Chapter 12 Introduction to Natural Language Processing
Chapter 13 Topic Modeling and Sentiment Analysis in NLP
Chapter 14 A Brief Introduction to Deep Learning and TensorFlow
Chapter 15 Creating a Machine Learning Architecture
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Get started in the field of Machine Learning with the help of this solid, concept-rich, yet highly practical guide.
Your one-stop solution for everything that matters in mastering the whats and whys of Machine Learning algorithms and their implementation.
Get a solid foundation for your entry into Machine Learning by strengthening your roots (algorithms) with this comprehensive guide.
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