Steven Taylor has 2 audiobooks on Listento.it, narrated by 1 narrator, with an average listener rating of 3★ across 1 ratings. The most-rated is Applied Predictive Modeling: An Overview.
Applied Predictive Modeling: An Overview
Summary
Predictive modeling uses statistics in order to predict outcomes. However, predictive modeling can be applied to events regardless of time of occurrence. When it comes to the applications of predictive modeling, techniques are used in various fields including algorithmic trading, uplift modeling, archaeology, health care, customer relationship management, and many others. This book covers the predictive modeling process with fundamental steps of the process, data preprocessing, data splitting and crucial steps of model tuning and improving model performance. Further, the book will introduce you to the most common classification and regression techniques including logistic regression which is widely used when it comes to the finding the probability of event success or event failure. You will get to know the common predictive modeling techniques as well such as stepwise regression, polynomial regression, and ridge regression which will help you when you are dealing with the data that suffers from very common multicollinearity where independent variables are highly correlated. What you will learn in Applied Predictive Modeling: Most common predictive modeling techniques Types of regression models The overall predictive modeling process Fundamental steps to effective and highly accurate predictive modeling How to build predictive model with logistic regression with code listings How to build predictive model using Python How to enhance your model performance Parameters for increasing the overall predictive power How to handle class imbalance Common causes of poor model performance Listen to this book now and learn more about applied predictive modeling!
©2017 Steven Taylor (P)2017 Steven Taylor
Markov Models: An Introduction to Markov Models
Summary
Markov Models This book will offer you an insight into the hidden Markov Models as well as the Bayesian networks. Additionally, by listening to this book, you will also learn algorithms such as Markov chain sampling. Furthermore, this book will also teach you how Markov models are very relevant when a decision problem is associated with a risk that continues over time, when the timing of occurrences is vital, as well as when events occur more than once. This book highlights several applications of Markov models. Lastly, after purchasing this book, you will need to put in a lot of effort and time for you to reap the maximum benefits. By listening to this book now, you will discover: Hidden Markov models Dynamic Bayesian networks Stepwise mutations using the Wright Fisher model Using normalized algorithms to update the formulas Types of Markov processes Important tools used with HMM Machine learning And much, much more! Download this book now, and learn more about Markov models!
©2017 Steven Taylor (P)2017 Steven Taylor