Original PDF Ebook – Mastering Machine Learning with scikit-learn – Second Edition2nd Edition – 9781788299879

Original PDF Ebook – Mastering Machine Learning with scikit-learn – Second Edition2nd Edition – 9781788299879

Use scikit-learn to apply machine learning to real-world problems_x000D_
About This Book_x000D_
Master popular machine learning models including k-nearest neighbors, random forests, logistic regression, k-means, naive Bayes, and artificial neural networks_x000D_
Learn how to build and evaluate performance of efficient models using scikit-learn_x000D_
Practical guide to master your basics and learn from real life applications of machine learning_x000D_
Who This Book Is For_x000D_
This book is intended for software engineers who want to understand how common machine learning algorithms work and develop an intuition for how to use them, and for data scientists who want to learn about the scikit-learn API. Familiarity with machine learning fundamentals and Python are helpful, but not required._x000D_
What You Will Learn_x000D_
Review fundamental concepts such as bias and variance_x000D_
Extract features from categorical variables, text, and images_x000D_
Predict the values of continuous variables using linear regression and K Nearest Neighbors_x000D_
Classify documents and images using logistic regression and support vector machines_x000D_
Create ensembles of estimators using bagging and boosting techniques_x000D_
Discover hidden structures in data using K-Means clustering_x000D_
Evaluate the performance of machine learning systems in common tasks_x000D_
In Detail