manikandan1408 Goto Github PK

apache-spark-projects

artificial-neural-nework-k-nearest-neighbors-for-sgemm-kernel-and-australian-weather-prediction-

feature-selection-k-means-and-expected-maximization-for-sgemm-and-australian-weather-dataset

To implement Feature selection, Dimensionality Reduction and use these features in Principal Component Analysis, Independent Component Analysis and Random Component Analysis for K Means, Expected Maximization and Neural network.

interviewprep

portfolio

Created portfolio using HTML and CSS

recommeding-items-to-customers-on-ecommerce

sentimental-analysis-of-imdb-movie-reviews

Dataset containing IMDB movie reviews and sentiments are filtered out to remove stopwords, html strips and noisy text and predicted the number of positive and negative reviews by performing Logistic Regression and Naive Bayes algorithm

sgemm-kernel-performance-using-linear-and-logistic-regression

Predicted the run time GPU Kernel by generating Linear and Logistic Regression models by implementing the Gradient Descent algorithm and experimented with different values of threshold and learning rate.

svm-decision-tree-for-sgemm-kernel-and-australia-weather-prediction

Compared performance with different Support Vector Machine kernels and Decision tree

tableau-visualization-of-different-disasters-affecting-exxon-refineries

Collected data on different Exxon refineries in the USA, located their counties and analyzed which all disasters are impacting the refinery locations. Identified the top 4 disasters and presented it as a story. This helps to know the advent of disasters to refinery companies before hand and they could plan appropriate measures to tackle them.

telecom-churn-analysis

Predicted the risk of churning using Logistic Regression and Random Forest

user-engagement-analysis