•Machine learning is an artificial intelligence (AI) discipline geared toward the technological development of human knowledge.
•Machine learning allows computers to handle new situations via analysis, self-training, observation and experience.
•With Machine Learning, computers are programmed to learn to do something they are not programmed to do:
•They literally learn by discovering patterns and insights from data.
• In general, we have two types of learning, supervised and unsupervised.
•.While Machine Learning is a subset of AI, we also have subsets within the domain of Machine Learning, including neural networks, natural language processing (NLP), and deep learning.
•Each of these subsets offers an opportunity for specializing in a career field that will only grow.
•Machine Learning is rapidly being deployed in all kinds of industries, creating a huge demand for skilled professionals.
• Machine Learning applications are used for data analytics, data mining and pattern recognition.
•On the consumer end, Machine Learning powers web search results, real-time ads, and network intrusion detection, to name only a few of the many tasks it can do.
•It's difficult to replicate human intuition in a machine, primarily because human beings often learn and execute decisions unconsciously.
•Like children, machines require an extended training period when developing broad algorithms geared toward the dictation of future behavior.
•Training techniques include rote learning, parameter adjustment, macro-operators, chunking, explanation-based learning, clustering, mistake correction, case recording, multiple model management, back propagation, reinforcement learning and genetic algorithms.
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