Mastering Predictive Analytics with scikit-learn and TensorFlow: Implement machine learning techniques to build advanced predictive models using Python
By 作者: Alvaro Fuentes
ISBN-10 书号: 178961774X
ISBN-13 书号: 9781789617740
Release Finelybook 出版日期: 2018-09-29
pages 页数: (154 )
Book Description to Finelybook sorting
Python is a programming language that provides a wide range of features that can be used in the field of data science. Mastering Predictive Analytics with scikit-learn and TensorFlow covers various implementations of ensemble methods, how they are used with real-world datasets, and how they improve prediction accuracy in classification and regression problems.
This book starts with ensemble methods and their features. You will see that scikit-learn provides tools for choosing hyperparameters for models. As you make your way through the book, you will cover the nitty-gritty of predictive analytics and explore its features and characteristics. You will also be introduced to artificial neural networks and TensorFlow, and how it is used to create neural networks. In the final chapter, you will explore factors such as computational power, along with improvement methods and software enhancements for efficient predictive analytics.
By the end of this book, you will be well-versed in using deep neural networks to solve common problems in big data analysis.
1: ENSEMBLE METHODS FOR REGRESSION AND CLASSIFICATION
2: CROSS-VALIDATION AND PARAMETER TUNING
3: WORKING WITH FEATURES
4: INTRODUCTION TO ARTIFICIAL NEURAL NETWORKS AND TENSORFLOW
5: PREDICTIVE ANALYTICS WITH TENSORFLOW AND DEEP NEURAL NETWORKS
What You Will Learn
Use ensemble algorithms to obtain accurate predictions
Apply dimensionality reduction techniques to combine features and build better models
Choose the optimal hyperparameters using cross-validation
Implement different techniques to solve current challenges in the predictive analytics domain
Understand various elements of deep neural network (DNN) models
Implement neural networks to solve both classification and regression problems
Alan Fontaine is a Data Scientist with more than 12 years of experience in analytical roles. He has been a consultant for many projects in fields such as: Business, Education, Medicine, Mass Media, among others.
He is a big Python fan and has been using it routinely for five years for analyzing data, building models, producing reports, making predictions and build interactive applications that transform data into intelligence.