Machine Learning for Beginners: Learn to Build Machine Learning Systems Using Python

Harsh Bhasin

Informasi Umum

Kode

21.21.012

Klasifikasi

006.31 - Machine Learning

Jenis

Buku - Elektronik (E-Book)

Subjek

Machine Learning

No. Rak

4

Informasi Lainnya

Abstraksi

This book covers important concepts and topics in Machine Learning. It begins with Data Cleansing and presents an overview of Feature Selection. It then talks about training and testing, cross-validation, and Feature Selection. The book covers algorithms and implementations of the most common Feature Selection Techniques. The book then focuses on Linear Regression and Gradient Descent. Some of the important Classification techniques such as K-nearest neighbors, logistic regression, Naïve Bayesian, and Linear Discriminant Analysis are covered in the book. It then gives an overview of Neural Networks and explains the biological background, the limitations of the perceptron, and the backpropagation model. The Support Vector Machines and Kernel methods are also included in the book. It then shows how to implement Decision Trees and Random Forests.

Towards the end, the book gives a brief overview of Unsupervised Learning. Various Feature Extraction techniques, such as Fourier Transform, STFT, and Local Binary patterns, are covered. The book also discusses Principle Component Analysis and its implementation.