Advanced Techniques for Multivariate Data by César Pérez López(.ePUB)+

Posted on by

File Size: 41.1 MB

Advanced Techniques for Multivariate Data Analysis Using Python. Predictive Models for Classification and Segmentation by César Pérez López
Requirements: .ePUB, .PDF reader, 41.1 MB
Overview: This book develops multivariate predictive or dependency analysis techniques (supervised learning techniques in the modern language of Machine Learning) and more specifically classification techniques from a methodological point of view and from a practical point of view with applications through Python software. The following techniques are studied in depth: Generalised Linear Models (Logit, Probit, Count and others), Decision Trees, Discriminant Analysis, K-Nearest Neighbour (kNN), Support Vector Machine (SVM), Naive Bayes, Ensemble Methods (Bagging, Boosting, Voting, Stacking, Blending and Random Forest), Neural Networks, Multilayer Perceptron, Radial Basis Networks, Hopfield Networks, LSTM Networks, RNN Recurrent Networks, GRU Networks and Neural Networks for Time Series Prediction. These techniques are a fundamental support for the development of Artificial Intelligence.
Genre: Non-Fiction > Tech & Devices

Free Download links:

https://trbt.cc/ufnnl8b0m4lq.html

https://katfile.com/h7b9onmft9sj/Advanced_Techniques_for_Multivariate_Data_Analysis.rar.html