Title
Mastering Predictive Analytics with scikitlearn and TensorFlow,Used
Delivery time: 8-12 business days (International)
Learn advanced techniques to improve the performance and quality of your predictive models Key Features Use ensemble methods to improve the performance of predictive analytics models Implement feature selection, dimensionality reduction, and crossvalidation techniques Develop neural network models and master the basics of deep learning Book DescriptionPython 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 scikitlearn and TensorFlow covers various implementations of ensemble methods, how they are used with realworld 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 scikitlearn provides tools for choosing hyperparameters for models. As you make your way through the book, you will cover the nittygritty 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 wellversed in using deep neural networks to solve common problems in big data analysis. 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 crossvalidation 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 Who this book is forMastering Predictive Analytics with scikitlearn and TensorFlow is for data analysts, software engineers, and machine learning developers who are interested in implementing advanced predictive analytics using Python. Business intelligence experts will also find this book indispensable as it will teach them how to progress from basic predictive models to building advanced models and producing more accurate predictions. Prior knowledge of Python and familiarity with predictive analytics concepts are assumed. Table of Contents Ensemble Methods for Regression and Classification Crossvalidation and Parameter Tuning Working with Features Introduction to Artificial Neural Networks and TensorFlow Predictive Analytics with TensorFlow and Deep Neural Networks
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Shipping & Returns
Shipping
We ship your order within 2–3 business days for USA deliveries and 5–8 business days for international shipments. Once your package has been dispatched from our warehouse, you'll receive an email confirmation with a tracking number, allowing you to track the status of your delivery.
Returns
To facilitate a smooth return process, a Return Authorization (RA) Number is required for all returns. Returns without a valid RA number will be declined and may incur additional fees. You can request an RA number within 15 days of the original delivery date. For more details, please refer to our Return & Refund Policy page.
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Warranty
We provide a 2-year limited warranty, from the date of purchase for all our products.
If you believe you have received a defective product, or are experiencing any problems with your product, please contact us.
This warranty strictly does not cover damages that arose from negligence, misuse, wear and tear, or not in accordance with product instructions (dropping the product, etc.).
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Your payment information is processed securely. We do not store credit card details nor have access to your credit card information.
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