Nidhi Mishra's Projects
Running A/B Test for Website on data for their two different pages to decide which page is more engaging to customers.
A collection of questions and solutions to problems presented at Rasmus Bååth's Bayesian probabilities workshop.
Programming Assignments of Machine Learning course by Andrew Ng in Python
We are using a Loan Prosper Data to find interesting relations between its various components using Data Visualization.
Projects done in the Data Engineering Nanodegree by Udacity.com
Implementing all sorting and search algorithms in Python.
Virtual Internship from InsideShapera with Quantium
A simple project using pandas, numpy and matplotlib to investigate IMDB dataset on movies
aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
Solutions for problems on www.projecteuler.net
This repository Includes Data Analysis of Engineering Colleges of India, Data Analysis of a Sports Facility using SQL, Data Analysis of Financial market Data using Quandle API. Skills used in this project are Requests Library, Data wrangling, Data Analysis of GSS(Global Social Survey) dataset using R and Hypothesis Test(Chi - Squared Test) and Data Analysis of Json Data.
Few projects related to Data Engineering including Data Modeling, Infrastructure setup on cloud, Data Warehousing and Data Lake development.
This repo is dedicated to the all the codes and Projects I make using various ML algos during the Udemy ML course by Kirill.
In this project we are analyzing a popular twitter page @dog_rates which is provided as a .csv file from Twitter archive. Tweepy is the API which is used as interface to the twitter API to download JSON data about retweet counts and favorite counts. We also need to download a file from Udacity servers using http request which predicts if the images are of dogs are not. We will be gathering, assessing and cleaning the data
Analyzing the Zomato dataset to get a fair idea about the factors affecting the establishment of different types of restaurant at different places in Bengaluru and aggregate rating of each restaurant.