Machine Learning Algorithms : Download Free Book
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This book is basically an introductory book for Machine Learning and Knowledge Discovery in Databases. It tries to show how one can learn to master two subjects - machine learning and knowledge discovery in databases - by getting a firm grasp on the theoretical and practical aspects of one of them. This book consists of two major parts: i) Understanding of Machine Learning, and ii) Striving to make Machine Learning and Knowledge Discovery in Databases More Automatic.
In this book, we focus on classical architectures for modelling complex real world problems arising in the field of machine learning. We take up several real world problems in depth, and examine their formalizations in graph-based models, as well as in feature-based models. We also solve such problems using a wide range of machine learning algorithms. In addition, we also explore the limitations of Graph based models and Feature based models.
To learn a decently fast model of a problem can be achieved by hand-coding. But for the deep learning models of today, you have to write a huge number of lines of code. Building these lines of code is akin to developing a software product - often time consuming and wallet straining! In this book, we study the trade-off between simplicity and accuracy. In other words, how can one use a small fraction of the code written by experts to achieve the ultimate performance? In this book, we define algorithms that need shallow models and are easy to implement. We use sophisticated statistical methods to verify their accuracy. We show how to build these algorithms by hand when the surface complexity of the model is low.
This book is written by a chemist and theoretically trained in mathematics. This book has chapters on various algorithms, organized in 6 parts. The first part deals with the basic concepts of Data Mining. The next one discusses classification, regression, clustering and association modeling. It will help you understand how to fit various types of model to your data. Through out this book, I have tried to incorporate the concepts of different algorithms. Preferably, it should not be hard to understand. 7211a4ac4a
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