Kmc 101/201 Artificial Intelligence for Engineering Unit-1 An overview to ai



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Artificial Intelligence for Engineering Notes Unit 1
Artificial Intelligence
Machine Learning
Artificial intelligence is a technology which enables a machine to simulate human behavior. Machine learning is a subset of AI which allows a machine to automatically learn from past data without programming explicitly. In AI, we make intelligent systems to perform any task like a human. In ML, we teach machines with data to perform a particular task and give an accurate result. AI system is concerned about maximizing the chances of success. Machine learning is mainly concerned about accuracy and patterns. AI has a very wide range of scope. Machine learning has a limited scope. The goal of AI is to make a smart computer system like humans to solve complex problems. The goal of ML is to allow machines to learn from data so that they can give accurate output.


Machine Learning
Deep Learning
Machine learning uses algorithms to parse data, learn from that data, and make informed decisions based on what it has learned
Deep learning structures algorithms in layers to create an artificial neural network that can learn and make intelligent decisions on its own
Can train on lesser training data
Requires large data sets for training
Takes less time to train
Takes longer time to train
Trains on CPU
Trains on GPU for proper training
Some algorithms are easy to interpret (logistic, decision tree, some are very difficult Complex to very complex algorithms
Other emerging technologies


RPA (Robotic Process Automation) RPA Training Robotic process automation (or RPA) is a form of business process automation technology based on metaphorical software robots bots) or on artificial intelligence (AI)/digital workers. It is sometimes referred to as software robotics. Automating repetitive tasks saves time and money. Robotic process automation bots expand the value of an automation platform by completing tasks faster, allowing employees to perform higher-value work.

Big Data Big Data, just as the phrase implies, is simply huge or large or broad or complex or a high amount of a specific set of information which can be understood by, and stored in a computer machine. Professionally, Big Data is afield that studies various means of extracting, analyzing, or dealing with sets of data that are so complex to be handled by traditional data-processing systems. Such an amount of data requires a system designed to stretch its extraction and analysis capability. The ideal and most effective means of handling Big Data is with AI. Our world is already steeped in Big Data. There is a massive amount of data online and offline about any topic you can think of, ranging from people, their routine, their preferences, etc to nonliving things, their properties, their uses, etc.


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