Nimesh Katoriwala's repositories
Image-Classification
Image classification using VGG 16
A-Paper-Review---Sentiment-Analysis
A Paper Reviews - A sentiment analysis. It was a Natural Language Processing project. The dataset consist of paper reviews sent to an international conference mostly reviews are in spanish and some are in english. All instances evaluated with a 5-point scale like: Positive, Highly Positive, Negative, Highly Negative and Neutral. I have applied multiple machine learning model such as: Logistic Regression, Naive Bayes and SVM.
Analytics-Vidhya-Hackathon---To-cross-sell-target-the-customer
The project was Analytics Vidhya Hackathon to predict the most likely customer for the loan. The dataset consist of 500000 instances and 330 features. A retail bank looking to improve their sales from existing customers. I have customer's personal informations with their assets, liabilities and transactions. For that I have used different machine learning classification model family algorithms.
auto-insurance-claims-detection
Predicting the fraud in auto insurance claims
AutoMl_WebApp
AutoML using Streamlit
Big-Data-Practice-Activity
This repositery is a practice repositery. The purpose of this repositery to help others who are new in big data. Here I including various code which are related to big data component like, Sqoop, Flume, Kafka, Hive, Pig, Pyspark, Machine Learning, MapReduce
Machine-Learning-Using-Big-Data-Component-PySpark
Objective is to classify/predict the CASE_STATUS using the machine learning model in pyspark.
NLP---SentimentAnalysis
Sentiment analysis for twitter chat
Policy-Bankruptcy
To predict whether the company bankrupted or not. The given problem is Classification Supervised Technique
Regression-Machin-Learning
All Regression Technique for Machine Learning
Unsupervised-Clustering-Technique
Unsupervised Technique Clustering, PCA
Used-Vehicle-Price-Prediction
To predict perfect price for used vehicle based on the given parameters. This is the Regression Supervised Problem.
Visualization-Using-R
Visualisation