114 results for "unsupervised learning"

Unsupervised learning is a type of AI-based machine learning that lets people get information from untargeted data sets. The machines find and manage unlabeled data so people are able to take advantage of complex tools, such as dimension reduction algorithms and clustering. The result of unsupervised learning is that users are able to identify patterns and results that emerge from a raw data set. Instead of entering a data set or goal, someone using unsupervised learning gets to let the data sets and patterns emerge to find the algorithm that makes the most sense.‎

If you enjoy solving complex puzzles and detecting hidden information to answer questions, learning about unsupervised learning puts it within your grasp to identify and present data in a coherent, usable manner. Learning how tools like dimensionality reduction algorithms and clustering let you break raw data into subsets and categories or clusters that can be used to create models. This makes the information usable for decision-making purposes as well as for directing supervised AI to explore specific data subsets. The categorized information becomes more relevant, and the characteristics of data clusters become more recognizable.‎

Data scientists and machine learning (AI) specialists are two career opportunities that can emerge from picking up the study of unsupervised learning. Before studying unsupervised learning, it helps to have Python programming knowledge and know the basics of calculus, data cleaning, probability, statistics, linear algebra, and exploratory data analysis because unsupervised learning builds upon these skills. You might work exclusively in the field of IBM machine learning strategies, or you may work in another field, such as engineering, customer market segmentation, data mining, or predictive analysis. Studying unsupervised learning helps you stay on top of developments in machine learning to stay relevant as well as advance in your career if you're already in the field.‎

The online unsupervised learning courses on Coursera give you the knowledge and practical experience about machine learning so you're able to use tools like k-means clustering, cluster analysis, and principle component analysis (PCA) to apply unsupervised machine learning techniques in a business setting. Apply these new skills and newly learned information to real-life business situations. Our online unsupervised learning courses provide the information and opportunity for you to develop a skill set that helps you reach your career goals or earn college credits at your own pace, and on your own terms.‎