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Practical Machine Learning Cookbook

You're reading from  Practical Machine Learning Cookbook

Product type Book
Published in Apr 2017
Publisher Packt
ISBN-13 9781785280511
Pages 570 pages
Edition 1st Edition
Languages
Author (1):
Atul Tripathi Atul Tripathi
Profile icon Atul Tripathi

Table of Contents (21) Chapters

Practical Machine Learning Cookbook
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
1. Introduction to Machine Learning 2. Classification 3. Clustering 4. Model Selection and Regularization 5. Nonlinearity 6. Supervised Learning 7. Unsupervised Learning 8. Reinforcement Learning 9. Structured Prediction 10. Neural Networks 11. Deep Learning 12. Case Study - Exploring World Bank Data 13. Case Study - Pricing Reinsurance Contracts 14. Case Study - Forecast of Electricity Consumption

Introduction


Electricity is the only commodity that is produced and consumed simultaneously; therefore, a perfect balance between supply and consumption in the electricity power market must always be maintained. Forecasting electricity consumption is of national interest to any country since electricity is a key source of energy. A reliable forecast of energy consumption, production, and distribution meets the stable and long-term policy. The presence of economies of scale, focus on environmental concerns, regulatory requirements, and a favorable public image, coupled with inflation, rapidly rising energy prices, the emergence of alternative fuels and technologies, changes in life styles, and so on, has generated the need to use modeling techniques which capture the effect of factors such as prices, income, population, technology, and other economic, demographic, policy, and technological variables.

Underestimation could lead to under-capacity utilization, which would result in poor quality...

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