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AI for Predictive Analytics: Forecasting with Machine Learning Using AI to analyze historical data and predict future trends for industries like finan
Paperback
Publisher: Independently Published
Published: Mar 16 2025
Pages: 260
Weight: 0.78
Height: 0.55 Width: 6.00 Depth: 9.00
Language: English
AI for Predictive Analytics: Forecasting with Machine Learning is your comprehensive guide to using artificial intelligence (AI) and machine learning (ML) for analyzing historical data and predicting future trends. This book explores the powerful role of AI in predictive analytics and how it is transforming industries like finance, healthcare, retail, and beyond by turning data into actionable insights.
With clear explanations, practical examples, and hands-on tutorials, you'll learn how to apply AI and ML algorithms to forecast trends, make data-driven decisions, and optimize business operations. Whether you're a data scientist, analyst, or business leader, this book will equip you with the tools to leverage predictive analytics for success in your industry.
Inside, you'll discover:
- Introduction to Predictive Analytics: Understand the basics of predictive analytics and the role AI plays in analyzing historical data to forecast future outcomes. Learn how predictive modeling and forecasting are applied in real-world scenarios.
- Machine Learning Algorithms for Forecasting: Dive into the machine learning algorithms used for predictive analytics, such as linear regression, decision trees, random forests, and neural networks. Learn how these algorithms help identify patterns and make predictions based on past data.
- Preparing Data for Predictive Modeling: Learn the importance of data cleaning, preprocessing, and feature engineering in building accurate predictive models. Discover techniques for handling missing data, outliers, and scaling data for machine learning algorithms.
- Time Series Forecasting: Explore the principles of time series analysis and how machine learning can be applied to predict trends over time. Learn how to work with time series data, including seasonal and trend components, and build models for accurate forecasting.
- Predictive Analytics in Finance: Discover how AI and machine learning are used in the finance industry for credit scoring, risk management, stock market prediction, and fraud detection. Learn how to apply predictive models to financial datasets for better decision-making.
- Predictive Analytics in Healthcare: Understand how predictive analytics is revolutionizing healthcare by forecasting patient outcomes, disease progression, and treatment efficacy. Learn how AI models are used in diagnostics, personalized medicine, and resource allocation.
- Evaluating and Improving Predictive Models: Learn how to evaluate the accuracy of predictive models using performance metrics like RMSE, MAE, and R-squared. Discover techniques for tuning models and improving their predictive power through cross-validation and hyperparameter optimization.
- Advanced Techniques in Predictive Analytics: Delve into advanced machine learning methods, such as ensemble learning, deep learning, and reinforcement learning, and understand how these techniques can be applied to more complex predictive tasks.
- Deploying Predictive Models in Production: Learn how to deploy machine learning models into production environments, manage model performance over time, and update models as new data becomes available.
- Ethical Considerations in Predictive Analytics: Explore the ethical implications of predictive analytics, including data privacy, algorithmic bias, and transparency in decision-making. Understand the importance of fairness and accountability in AI-driven predictions.
By the end of this book, you'll be well-equipped to use AI and machine learning for predictive analytics, forecast trends, and make data-driven decisions in industries like finance, healthcare, and more.
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AP Computer Science Principles Premium, 2027: 6 Practice Tests + Comprehensive Review + Online Practice
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AI for Educators: Learning Strategies, Teacher Efficiencies, and a Vision for an Artificial Intelligence Future
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RHCSA Red Hat Enterprise Linux 10: Training and Exam Preparation Guide (EX200), Fourth Edition
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More Human: How the Power of AI Can Transform the Way You Lead
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Graphic Artists Guild Handbook, 17th Edition: Pricing & Ethical Guidelines
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Microsoft 365 Excel All-In-One for Dummies
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The Coming Wave: Technology, Power, and the Twenty-First Century's Greatest Dilemma
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Navigeren door het labyrint: Een handleiding voor het beheer van data
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Hbr's 10 Must Reads on Artificial Intelligence, Updated and Expanded (Featuring How AI Can Help Managers Think Through Problems by Elisa Farri and Gab
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Prediction Machines, Updated and Expanded: The Simple Economics of Artificial Intelligence
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The Empty Center: Permission, Connection, and What We Build When the Future is Uncertain
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Laptops for Seniors in Easy Steps, 9th Edition: Covers All Laptops with the Windows 11 2024 Update
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The Next Big Thing: Innovations for a Better, Smarter, Stronger Tomorrow
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A Whole New Human: Ten Ways We Must Evolve to Survive and Thrive in the AI Age
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R for Data Science: Import, Tidy, Transform, Visualize, and Model Data
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Cetinkaya-Rundel, Mine
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On the Future of Species: Authoring Life by Means of Artificial Biological Intelligence
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Comptia A+ Complete Study Guide, 2-Volume Set: Volume 1 Core 1 Exam 220-1201 and Volume 2 Core 2 Exam 220-1202
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Rewiring Democracy: How AI Will Transform Our Politics, Government, and Citizenship
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Hardcover