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K-means clustering in machine learning is one of the most simple yet powerful unsupervised machine learning algorithms. K-means clustering in machine learning works by creating a centroid for a desired number of classes and then assigning data points to clusters based on which reference point is closest. One of the crucial caveats of K-means algorithms is choosing the value of K. Read more on this link
K-means clustering is an unsupervised algorithm which you can use to organise large amounts of retail data to generate competitive insights about your business. There are many use cases which can help you implement this practice in your business and compete strategically in the retail market. But how can you use a k-means clustering algorithm effectively toRead more on this link
While analyzing the data, the thing in our mind is to find hidden patterns and extract meaningful insights. Let’s enter into the new category of ML-based learning, i.e., Unsupervised learning, in which one of the powerful algorithms to solve the clustering tasks is the K-Means clustering algorithm which revolutionizes data Read more on the link
Clustering is one of the most common exploratory data analysis technique used to get an intuition about the structure of the data. It can be defined as the task of identifying subgroups in the data such that data points in the same subgroup (cluster) are very similar while data points in different clusters are very different. In othe Read more on the link
Have you ever wondered what forms the basis of May I know you page that facebook directed you when you were busy scrolling through or how your online signatures are verified ?Remember the crime documentaries whereRead more on the link
Neural networks are a powerful tool for data scientists, machine learning engineers, and statisticians. They have revolutionized the field of machine learning and have become an integral part of many real-world aRead more on the link
ABC analysis assumes that revenue-generating items in an inventory follow a Pareto distribution, where a very small percent of items generate the most amount of revenue. Using the following conventions, an item in inventory is assigned a letter based on importanceRead more on the link
A neural network is a series of algorithms that endeavors to recognize underlying relationships in a set of data through a process that mimics the way the human brain operates. This means that neural networks can be able to do learn and process the data in the same way that.Read more on the link
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