Dynamic Programming in a #rightapproch It was really a great session by our mantor Vimal sir, this session was long but it give me a new way of thing how to deep dive into something and know the answer of advance from the core one.it give me gave me the one most very intresting scene of very popular movies 3 idiot where amair khar tell to the proffecer that he teach him "how to teach",every indian mind set is to come top by anyhow by sitting and chanting topic like bhajans ,we never have intrest in knowing how the thing work as that sir tell us in his session .it was really a life changing session just the 2 day session affect my mind soo deeply .i'm really thankful to vimal sir for this wounderful session and at last i'm really eager to be a part of Arth 2.0 and i'm really excited for it and started updating my knowlege and laptop too..... #dynamicprogramming #dp #programming #dsa #mastersession #righteducation #vimaldaga #worldrecordholder #dpbylw
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K-mean clustering and the Security domain.
Clustering Clustering is an unsupervised algorithm to discover groups of similar things, ideas, or people. Unlike supervised algorithms, we're not training clustering algorithms with examples of known labels. Instead, clustering tries to find structures within a training set where no point of the data is the label. K-Means Clustering K-Means is a clustering algorithm with one fundamental property: the number of clusters is defined in advance . In addition to K-Means, there are other types of clustering algorithms like Hierarchical Clustering, Affinity Propagation, or Spectral Clustering. How K-Means Works Suppose our goal is to find a few similar groups in a dataset like: K-Means begins with k randomly placed centroids. Centroids, as their name suggests, are the center points of the clusters . For example, here we're adding four random centroids: Then we assign each existing data point to its nearest centroid: After the assignment, we move the centroids to the average ...