Machine Learning for Decision Makers: Cognitive Computing Fundamentals for Be…
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Machine Learning for Decision Makers: Cognitive Computing Fundamentals for Beginners
Are you a decision maker looking to leverage the power of machine learning and cognitive computing in your organization, but unsure where to start? This post is for you.
Machine learning is a subset of artificial intelligence that involves the development of algorithms that enable computers to learn from and make predictions or decisions based on data. Cognitive computing, on the other hand, goes a step further by attempting to mimic the way the human brain works, using natural language processing, image recognition, and other techniques to understand and interact with humans in a more natural way.
In this post, we will cover the basics of machine learning and cognitive computing, including:
– The difference between supervised and unsupervised learning
– Common machine learning algorithms, such as decision trees, support vector machines, and neural networks
– How to evaluate the performance of a machine learning model
– The potential applications of cognitive computing in various industries, from healthcare to finance to retail
By understanding these fundamentals, you will be better equipped to make informed decisions about how to incorporate machine learning and cognitive computing into your organization’s strategy. Stay tuned for more in-depth posts on specific use cases and best practices for implementing these technologies in your business.
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