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Machine Learning in Action
Price: $47.49
(as of Dec 27,2024 04:49:12 UTC – Details)
ASIN : B09781SJJ7
Publisher : Manning; 1st edition (April 3, 2012)
Publication date : April 3, 2012
Language : English
File size : 8776 KB
Text-to-Speech : Enabled
Screen Reader : Supported
Enhanced typesetting : Enabled
X-Ray : Not Enabled
Word Wise : Not Enabled
Print length : 384 pages
Customers say
Customers find the book provides a good introduction to machine learning techniques and algorithms. They find it a valuable starting point for implementing them. However, some readers report issues with editing quality and readability. Some find the text easy to understand and well-written, while others describe it as poorly written, repetitive, and difficult to read.
AI-generated from the text of customer reviews
Machine Learning in Action: How AI is revolutionizing industries
Machine learning, a subset of artificial intelligence, is rapidly transforming various industries by allowing computers to learn from data and make decisions without explicit programming. From healthcare to finance to transportation, machine learning is being used to improve efficiency, accuracy, and decision-making.
In healthcare, machine learning algorithms are being used to analyze medical images, identify patterns in patient data, and even predict disease outbreaks. This technology is enabling doctors to make faster and more accurate diagnoses, ultimately saving lives.
In finance, machine learning is being used to detect fraud, predict stock market trends, and optimize trading strategies. Banks and financial institutions are leveraging this technology to improve risk management and increase profits.
In transportation, machine learning is being used to optimize routes, predict traffic patterns, and enhance safety. Companies like Uber and Lyft are using machine learning algorithms to match drivers with passengers, minimize wait times, and reduce congestion on the roads.
Overall, machine learning is revolutionizing industries by automating processes, uncovering insights from data, and improving decision-making. As this technology continues to advance, we can expect to see even more innovative applications across various sectors.
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