“Rishi is a quick learner with the ability to work efficiently in a team set up. Rishi and I were project partners and I endorse Rishi's ability to quickly come up with a solution. He is an enthusiastic programmer with a good grasp on Python. Rishi would be an asset to any team. I strongly recommend him for roles in the field of Analytics.”
About
• Data Science professional with 4+ years of experience in Causal Inference, Machine…
Activity
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What an insightful experience at TSIA conference in Orlando! One of the key takeaways: the growing influence of AI in the technology and services…
What an insightful experience at TSIA conference in Orlando! One of the key takeaways: the growing influence of AI in the technology and services…
Liked by Rishi Nandhan Prasad Kavitha
Experience & Education
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Amazon
View Rishi Nandhan’s full experience
See their title, tenure and more.
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Licenses & Certifications
Courses
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Cryptography and Network Security
CS6701
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Data Preparation
STA6714
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Database and Management Systems
CS6302
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Discrete Mathematics
MA6566
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Graph Theory and Applications
CS6702
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Grid and Cloud Computing
CS6703
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Interactive Data Visualization
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Machine Learning
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Network Science
CNT5805
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Probability and Queuing Theory
MA6453
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Resource Management Techniques
CS6704
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Statistical Analysis
STA5206
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Transforms and Partial Differential Equation
MA6351
Projects
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Predicting Term Deposit- R Language
Predicting whether a bank customer will or will not enroll in term deposit based on a few predictors and implementing machine learning models.
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Visualization of Graduate Admission- R and Tableau
Analyzing and preprocessing the Graduate Admission data set in R, finding the importance of each variable and visualizing in tableau showing how each predictor influence the output.
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Sentiment Classification using Naive Bayes Classification- Python
Implemented text classification on the sample data set and classified the text to be positive or negative by using Naive Bayes Classifier code.
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Predicting the Liver Condition- R Language
Predicting the condition of patients’ liver as affected or not by using Machine Learning algorithms.
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Twitter Analysis on US Airlines
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Removed the punctuations, stop words, Lemmatized the words and spell checked each word in the data.
Converted the data to tf-idf vectorizer and count vectorizer.
Implemented Random forest classifier and Naïve Bayes classifier and achieved an accuracy score of 77% -
Image Classification using Convolution Neural Network- Python
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Created an CNN architecture with many Convolution layer and Max pooling layer. Started the
architecture with 100 filters and reduced gradually as layers increased.
Trained the model with 6000 images and achieved an accuracy of 75.33% with a model loss of 0.62. -
Sentiment Classification using Logistic Regression- Python
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Text classification is implemented on positive and negative files and implemented Logistic Regression model.
Test Scores
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Graduate Record Examinations (GRE)
Score: 306
QUANTS - 164
VERBAL - 142
Languages
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Tamil
Native or bilingual proficiency
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English
Full professional proficiency
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