Lemmatization: implementation using Python

For Reducing morphological variations and grouping words to one common root JIRA CODE – JJ-134 It is the process of grouping together the different inflected forms of a word so they can be analysed as a single item. Lemmatization is similar to stemming but it brings context to the words. So it links words with… Continue reading Lemmatization: implementation using Python

Backbone.View

Backbone views are almost more convention than they are code — they don’t determine anything about your HTML or CSS for you, and can be used with any JavaScript templating library. The general idea is to organize your interface into logical views, backed by models, each of which can be updated independently when the model… Continue reading Backbone.View

Stemming: Implementation using Python code

A normalizing method in Python JIRA CODE: JJ-134 Stemming:The idea of stemming is a sort of normalizing method. Many variations of words carry the same meaning, other than when tense is involved.There are mainly two errors in stemming – Over stemming and Under stemming. Over stemming occur when two words are stemmed to same root… Continue reading Stemming: Implementation using Python code

Backbone.Collection

Collections are ordered sets of models. You can bind “change” events to be notified when any model in the collection has been modified, listen for “add” and “remove” events, fetch the collection from the server, and use a full suite of Underscore.js methods. Any event that is triggered on a model in a collection will also be triggered on the collection directly, for convenience.… Continue reading Backbone.Collection

K-Nearest Neighbor Algorithm(K-NN Algorithm) in Python

Implementation code of K-NN Algorithm using Python language JIRA CODE – JJ – 134 This algorithm is used to solve the classification model problems. K-nearest neighbor or K-NN algorithm basically creates an imaginary boundary to classify the data. When new data points come in, the algorithm will try to predict that to the nearest of… Continue reading K-Nearest Neighbor Algorithm(K-NN Algorithm) in Python

Naive Bayes Algorithm in Python

Bayes’ Theorem provides a way that we can calculate the probability of a piece of data belonging to a given class. Bayes’ Theorem is stated as: P(class|data) = (P(data|class) * P(class)) / P(data) Where P(class|data) is the probability of class given the provided data. Naive Bayes is a classification algorithm for binary (two-class) and multiclass… Continue reading Naive Bayes Algorithm in Python

Web scraping: implementation using Python

Web scraping is used to collect large information from websites.JIRA CODE – JJ – 134 Web scraping is an automated method used to extract large amounts of data from websites. The data on the websites are unstructured. Web scraping helps collect these unstructured data and store it in a structured form. Steps of Web Scrapping:… Continue reading Web scraping: implementation using Python

Payroll For NetSuite

Jira Code: GLL-8 Case study for the implementation of a payroll system in NetSuite according to the AU, UK, and US requirements. Possibly in a single system. Paycheck Journal feature : Supports countries other than the U.S. for having access  to different  payroll capabilities, including the tracking of payroll data for employees.  Paycheck  Journal  feature… Continue reading Payroll For NetSuite