Название: Building Machine Learning Systems Using Python: Practice to Train Predictive Models and Analyze Machine Learning ResultsАвтор: Deepti Chopra
Издательство: BPB Publications,
Год: 2021
Формат: ePUB, PDF
Страниц: 247
Размер: 10 Mb
Язык: English
This book covers basic concepts of Machine Learning, various learning paradigms, different architectures and algorithms used in these paradigms.
You will learn the power of ML models by exploring different predictive modeling techniques such as Regression, Clustering, and Classification. You will also get hands-on experience on method and techniques such as Overfitting, Underfitting, Random Forest, Decision Trees, PCA, and Support Vector Machines. In this book real life examples with fully working of Python implementations are discussed in detail.
At the end of the book you will learn about the unsupervised learning covering Hierarchical Clustering, K-means Clustering, Dimensionality Reduction, Anomaly detection, Principal Component Analysis.
What you will learn
● Learn to perform data engineering and analysis.
● Build prototype ML models and production ML models from scratch.
● Develop strong proficiency in using scikit-learn and Python.
● Get hands-on experience with Random Forest, Logistic Regression, SVM, PCA, and Neural Networks.