If You're Curious About These Questions...
You should listen to this audiobook
- Did you know that companies can actually predict your next move—from what you'll buy to when you might quit your job—before you even realize it yourself?
- Have you ever wondered how a single line of code can help doctors save lives or stop a bank robbery before it even happens?
- What’s the secret to turning massive piles of raw data into a 'crystal ball' that can forecast the future of global markets and personal health?
Listen to Predictive Analytics — Free Audiobook
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Key Takeaways from Predictive Analytics
- Understand how predictive analytics lowers business risks by using machine learning and backtesting to anticipate specific individual behaviors rather than general trends.
- Discover the ethical dilemmas and privacy concerns of data mining, including how predictive models can inadvertently enforce prejudice and racial profiling.
- Learn why an abundance of data requires careful balancing to avoid costly false correlations, like the statistical illusion that orange cars are less likely to break down.
- Explore how organizations leverage predictive scoring and everyday behavioral data to optimize targeted marketing, forecast investments, and even prevent localized crimes.
- Find out how machine learning empowers predictive models to continuously adapt and uncover disguised 'microrisks' that traditional analysis might overlook.
Learning Tools
Reinforce what you learned from Predictive Analytics
Mind Map
Predictive Analytics
Core Concepts & Functionality
Predicting Individual Behavior
Accuracy Mechanisms
Ethics, Privacy & Prejudice
Privacy Intrusions
Prejudice & Profiling
Data Quality & Balance
The Need for Balance
Textual Data
Machine Learning Risks & Rewards
Identifying Microrisks
The Danger of Overlearning
Ensemble Models & Crowdsourcing
The Ensemble Effect
Crowdsourcing Innovation
Natural Language Processing
Linguistic Challenges
IBM Watson Breakthrough
The Uplift Model & Persuasion
Quantifying Persuasion
Targeting Strategy
Quiz — Test Your Understanding
Question 1 of 8
What is the primary purpose of predictive analytics (PA) in a business context, according to the text?
Predictive Analytics — Full Chapter Overview
Chapter 1: Recommendation
Chapter 2: Predictive analytics helps you reduce risks and make smarter, safer decisions overall.
Chapter 3: Predictive efforts raise questions about responsibility, morality, and potential prejudice.
Chapter 4: Data is inherently predictive, but accuracy needs a well-balanced amount of data.
Chapter 5: Machine learning can reveal overlooked risks, yet risks to machine learning exist too and must be managed.
Chapter 6: Combining multiple data sources and models boosts accuracy and performance.
Chapter 7: Human language presents tough challenges, yet major advances have already arrived today.
Chapter 8: Predictive analytics identifies the imperceptible by measuring and quantifying persuasion.
Predictive Analytics Summary & Overview
Predictive Analytics (2016) provides a helpful introduction to a complex and fascinating field. Learn how data gets crunched so that people can make more informed decisions, a practice that has drastically altered the way the world conducts its research and runs its businesses. Siegel offers an enlightening glimpse at the wide-ranging areas that have been forever changed, from marketing to health care, banking to artificial intelligence.
Who Should Listen to Predictive Analytics?
- Business students interested in applied analytics
- Readers interested in economics
- Tech geeks curious about artificial intelligence
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