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Why Compassion Is a Better Managerial Tactic than Toughness

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Stanford University neurosurgeon Dr. James Doty tells the story of performing surgery on a little boy’s brain tumor. In the middle of the procedure, the resident who is assisting him gets distracted and accidentally pierces a vein. With blood shedding everywhere, Doty is no longer able to see the delicate brain area he is working on. The boy’s life is at stake. Doty is left with no other choice than to blindly reaching into the affected area in the hopes of locating and clamping the vein. Fortunately, he is successful.

Read more at HBR.org

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Machine Learning with Python: k-Means Clustering

Clustering—an unsupervised machine learning approach used to group data based on similarity—is used for work in network analysis, market segmentation, search results grouping, medical imaging, and anomaly detection. K-means clustering is one of the most popular and easy to use clustering algorithms. In this course, Fred Nwanganga gives you an introductory look at k-means clustering—how it works, what it’s good for, when you should use it, how to choose the right number of clusters, its strengths and weaknesses, and more. Fred provides hands-on guidance on how to collect, explore, and transform data in preparation for segmenting data using k-means clustering, and gives a step-by-step guide on how to build such a model in Python.

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