Treffer: Machine Learning Quick Reference: Quick and Essential Machine Learning Hacks for Training Smart Data Models.

Description based upon print version of record. ; Importing the library ; Machine learning involves development and training of models used to predict future outcomes. This book is a practical guide to all the tips and tricks related to machine learning. It includes hands-on, easy to access techniques on topics like model selection, performance tuning, training neural networks, time series analysis and a lot more. ; Cover; Title Page; Copyright and Credits; About Packt; Contributors; Table of Contents; Preface; Chapter 1: Quantifying Learning Algorithms; Statistical models; Learning curve; Machine learning; Wright's model; Curve fitting; Residual; Statistical modeling - the two cultures of Leo Breiman; Training data development data -- test data; Size of the training, development, and test set; Bias-variance trade off; Regularization; Ridge regression (L2); Least absolute shrinkage and selection operator ; Cross-validation and model selection; K-fold cross-validation ; Model selection using cross-validation0.632 rule in bootstrapping; Model evaluation; Confusion matrix; Receiver operating characteristic curve; Area under ROC; H-measure; Dimensionality reduction; Summary; Chapter 2: Evaluating Kernel Learning; Introduction to vectors; Magnitude of the vector; Dot product; Linear separability; Hyperplanes ; SVM; Support vector; Kernel trick; Kernel; Back to Kernel trick; Kernel types; Linear kernel; Polynomial kernel; Gaussian kernel; SVM example and parameter optimization through grid search; Summary; Chapter 3: Performance in Ensemble Learning ; What is ensemble learning?Ensemble methods ; Bootstrapping; Bagging; Decision tree; Tree splitting; Parameters of tree splitting; Random forest algorithm; Case study; Boosting; Gradient boosting; Parameters of gradient boosting; Summary; Chapter 4: Training Neural Networks; Neural networks; How a neural network works; Model initialization; Loss function; Optimization; Computation in neural networks; Calculation of activation for H1; Backward propagation; Activation ...