The Concept of CGI CGI is an abbreviation for Common Gateway Interface. It is not a type of language but a set of rules (specification) that establishes a dynamic interaction between a web application and the client application (or the browser). The programs based on CGI helps in communicating betweenContinue Reading

A regular expression is a set of characters with highly specialized syntax that we can use to find or match other characters or groups of characters. In short, regular expressions, or Regex, are widely used in the UNIX world. Import the re Module The re-module in Python gives full supportContinue Reading

Introduction to the Python regular expressions Regular expressions (called regex or regexp) specify search patterns. Typical examples of regular expressions are the patterns for matching email addresses, phone numbers, and credit card numbers. Regular expressions are essentially a specialized programming language embedded in Python. And you can interact with regularContinue Reading

Text Processing is one of the most common task in many ML applications. Below are some examples of such applications. • Language Translation: Translation of a sentence from one language to another.• Sentiment Analysis: To determine, from a text corpus, whether the sentiment towards any topic or product etc. isContinue Reading

Important Terms in Hierarchical Clustering Linkage Methods Suppose there are (a) original observations a[0],…,a[|a|−1] in cluster (a) and (b) original objects b[0],…,b[|b|−1] in cluster (b), then in order to combine these clusters we need to calculate the distance between two clusters (a) and (b). Say a point (d) exists thatContinue Reading

We usually start with K-Means clustering. After going through several tutorials and Medium stories you will be able to implement k-means clustering easily. But as you implement it, a question starts to bug your mind: how can we measure its goodness of fit? Supervised algorithms have lots of metrics to checkContinue Reading

A fundamental step for any unsupervised algorithm is to determine the optimal number of clusters into which the data may be clustered. The Elbow Method is one of the most popular methods to determine this optimal value of k.We now demonstrate the given method using the K-Means clustering technique using the Sklearn library ofContinue Reading

Introduction to Hierarchical Clustering Hierarchical clustering is another unsupervised learning algorithm that is used to group together the unlabeled data points having similar characteristics. Hierarchical clustering algorithms falls into following two categories − Agglomerative hierarchical algorithms − In agglomerative hierarchical algorithms, each data point is treated as a single cluster andContinue Reading

Introduction to Mean-Shift Algorithm As discussed earlier, it is another powerful clustering algorithm used in unsupervised learning. Unlike K-means clustering, it does not make any assumptions; hence it is a non-parametric algorithm. Mean-shift algorithm basically assigns the datapoints to the clusters iteratively by shifting points towards the highest density ofContinue Reading

Introduction to K-Means Algorithm K-means clustering algorithm computes the centroids and iterates until we it finds optimal centroid. It assumes that the number of clusters are already known. It is also called flat clustering algorithm. The number of clusters identified from data by algorithm is represented by ‘K’ in K-means. In thisContinue Reading