vaibhav-sing-bisht Goto Github PK

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Name: Vaibhav Singh Bisht

Type: User

Twitter: vaibhav271

Location: Lucknow

Vaibhav Singh Bisht's Projects

bank-customer-segmentation-and-insurance-claim-prediction

Course Data Mining The project involved drawing inferences from 2 case studies, namely - Bank Marketing & Insurance. The concepts of Clustering, CART, Random Forest, Artificial Neural Network are used to draw inferences from these case studies. Various performance metrics have been used to validate the performance of predictions on Test & Train sets. Skills and Tools Clustering, CART, Random Forest, Artificial Neural Networks

election-exit-poll-prediction-and-u.s.a-presidential-speech-analysis-using

Course Machine Learning This project is based on 2 case-studies: Vote Prediction and Text Analysis. The first project is to predict which party a citizen is going to vote for on the basis of their age and according to the answers given by the citizens to the questions asked in a survey conducted. The second project is based on the analysis of the inaugural U.S.A. Presidential speeches. One has to draw inferences based on the analysis done on these speeches. Skills and Tools Text Mining Analytics, Support Vector Machine - K Nearest Neighbour - Naive Bayes, Ensemble Techniques, Logistic Regression - Linear Discriminant Analysis

gems-holiday-package-prediction

This project is based on 2 cases studies : Gems Price Prediction and Holiday Package prediction. In the first case study, concepts of linear regression are tested and it is expected from the learner to predict the price of gems based on multiple variables to help company maximize profits. In the second case, concepts of logistic regression and linear discriminant analysis are tested. One has to predict if the customer will purchase the holiday package to target the relevant customer base. Skills and Tools Linear Regression, Logistic Regression, Linear discriminant Analysis

heart-disease-prediction-

This database contains 76 attributes, but all published experiments refer to using a subset of 14 of them. In particular, the Cleveland database is the only one that has been used by ML researchers to this date. The "goal" field refers to the presence of heart disease in the patient.

natural-language-processing

In this particular project, we are going to work on the inaugural corpora from the nltk in Python. We will be looking at the following speeches of the Presidents of the United States of America President Franklin D. Roosevelt in 1941 President John F. Kennedy in 1961 President Richard Nixon in 1973 Find the number of characters, words and sentences for the mentioned documents. Remove all the stopwords from all the three speeches. Which word occurs the most number of times in his inaugural address for each president? Mention the top three words. (after removing the stopwords) Plot the word cloud of each of the speeches of the variable. (after removing the stopwords) Code Snippet to extract the three speeches: " import nltk nltk.download('inaugural') from nltk.corpus import inaugural inaugural.fileids() inaugural.raw('1941-Roosevelt.txt') inaugural.raw('1961-Kennedy.txt') inaugural.raw('1973-Nixon.txt') "

shinkansen-travel-experience-gl-hackathon

The goal of the problem is to predict whether a passenger was delighted considering his/her overall travel experience of traveling in Shinkansen (Bullet Train).

time-series-forecasting

Analyzed historical monthly sales data of a company. Created multiple forecast models for two different products of a particular Wine Estate and recommended the optimum forecasting model to predict monthly sales for the next 12 months along with appropriate lower and upper confidence limits