Machine Learning and Science of Algorithms

I have complete course of Machine Learning and Science of Algorithms. Machine learning is used to gives us practical tools to analyze data. Machine learning is completely by using the right features to build the right models that achieve the right tasks. In this book you will learn different machine learning tricks and techniques that reveal invisible ideas and extremity for different types of data with the help of practical and real-world. In this book, you will learn a number of techniques to build machine learning applications that sort out varying real world problems, from document identification to image recognition. In this book you will learn about Science of Algorithm. Algorithm is defined as a set of instructions for solving a problem or realize a charge. Most important example of an algorithm is a recipe that comprise of particular commands for preparing a meal. Every cybernated devices that use algorithms to perform its functions.

In this book you will learn different topics in detail:

  • A machine learning sampler


  • The ingredients of machine learning


  • Binary classification and related tasks
  • Beyond binary classification
  • Concept learning
  • Tree models
  • Rule models
  • Linear models
  • Distance-based models
  • Probabilistic models
  • Features
  • Model ensembles
  • Machine learning experiments
  • Epilogue
  • Important points to remember


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