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Hi šŸ‘‹, I'm SHIVENDRA PARMAR

A passionate DATA SCIENTIST from India

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shivendraparm12 shivendra parmar shivendra parmar parmarshivendra1

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arduino c canvasjs cassandra chartjs cplusplus d3js gcp git grafana gridsome hive invision kibana linux mongodb mssql mysql opencv oracle pandas postgresql python pytorch scikit_learn scully seaborn tensorflow

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SHIVENDRA PARMAR's Projects

-imdb-director-insights icon -imdb-director-insights

IMDB, the world's most popular and authoritative source for movie, TV, and celebrity content, wants to provide more insights to its users about directors. Specifically, they want to offer users the ability to discover top-rated directors, their filmography, and other important details such as their awards and nominations.

airbnb_nps_calculation icon airbnb_nps_calculation

NPS is a measure of customer loyalty and satisfaction. It's determined based on responses to a simple question: "On a scale of 0 to 10, how likely are you to recommend Airbnb to a friend or colleague?" Here's how you can calculate Airbnb's NPS:

amex_default_prediction_eda- icon amex_default_prediction_eda-

Credit default prediction is central to managing risk in a consumer lending business. Credit default prediction allows lenders to optimize lending decisions, which leads to a better customer experience and sound business economics. Current models exist to help manage risk.

analytics icon analytics

Lightweight analytics abstraction layer for tracking page views, custom events, & identifying visitors

data-science-bootcamp icon data-science-bootcamp

Regular practice on Data Science, Machien Learning, Deep Learning, Solving ML Project problem, Analytical Issue. Regular boost up my knowledge. The goal is to help learner with learning resource on Data Science filed.

docs icon docs

The open-source repo for docs.github.com

dog_classification_ml_model icon dog_classification_ml_model

In this project, we'll walk through an end-to-end deep learning project using TensorFlow and Keras. We'll read in a dataset of dog images, then train a convolutional neural network to classify them by breed. By the end, you'll know how to use Keras to train and optimize a neural network.

employees_data_analysis icon employees_data_analysis

This repository is dedicated to analyzing and extracting valuable insights from employee datasets using SQL on MySQL Workbench. Understanding employee data is essential for effective human resource management and organizational decision-making. This project aims to explore and understand various aspects of employee data.

exploratory-data-analysis icon exploratory-data-analysis

Since I am a huge fan of cars, I got a very beautiful data-set of cars from Kaggle. The data-set can be downloaded from here. To give a piece of brief information about the data set this data contains more of 10, 000 rows and more than 10 columns

farmers_market_analysis icon farmers_market_analysis

Welcome to the Farmer Market Analysis repository, your go-to resource for comprehensive data analysis and insights into the agricultural market landscape. This repository serves as a hub for the code, datasets, and documentation related to our ongoing research and analysis of farmer markets.

fitbit_user_analysis icon fitbit_user_analysis

This project is a data analysis and insights project focused on Fitbit user data. Fitbit provides a range of wearable devices that track health and fitness metrics. This project leverages NumPy to analyze Fitbit user data and gain valuable insights into user behaviors, health trends, and more.

freecodecamp icon freecodecamp

freeCodeCamp.org's open-source codebase and curriculum. Learn to code for free.

grammars-v4 icon grammars-v4

Grammars written for ANTLR v4; expectation that the grammars are free of actions.

insurance-firm---eda icon insurance-firm---eda

This repository contains a comprehensive Exploratory Data Analysis (EDA) of an insurance firm's dataset. The analysis provides valuable insights into the age distribution of customers, the most frequent insurance fees, BMI distribution, detection of outliers in insurance charges, and various data relationships.

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