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Index
CHAPTER ONE
What is learning Types of Data They Deal With Predictive Power and Human Effort Essentiality of Machine Learning: How IoT can advantage from Machine Learning: Air quality and energy with Machine Learning: Wellsprings of Machine Learning Relations to Other Fields Few Useful Things to Know about Machine Learning When Do We Need Machine Learning? Important tips for machine learning
CHAPTER TWO
Problems associated with Machine Learning How can you find the best machine learning for you? What to Expect from a Machine Learning Engineer What are the steps used in Machine Learning? What’s the Difference between Machine Learning Techniques?
CHAPTER THREE
How machine learning personalization adds to your bottom line Ways AI Is Already Making a Difference in Society How Machine Learning Influences Your Productivity How does this work? How Machine Learning Is Improving Companies Work Processes
CHAPTER FOUR
Learning Input-Output Functions Input Vectors Outputs Training Regimes Not everything is Learnable The Importance of Good Features
CHAPTER FIVE
How edge computing and server less deliver scalable machine learning services Unconventional knowledge about machine learning that you can’t learn from books Hardware alternative for ML and AI quantum computing
CHAPTER SIX
Importance of Algorithm in programming, AI, and machine lemming Advantages of using Algorithms The Algorithms machine learning Engineers need to know Supervised Learning Unsupervised Learning Machine learning techniques for predictive maintenance Machine Learning Implementation Machine learning market growth and trends
INDEX
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