Pinned Repositories
2014
Official content for the Fall 2014 Harvard CS109 Data Science course
2014_data
Data directory for the CS109 Data Science course
AuthorProfiling
Predict gender and age of author from text
awesome-courses
:books: List of awesome university courses for learning Computer Science!
awesome-scalability
The Patterns of Scalable, Reliable, and Performant Large-Scale Systems
B551-Artificial-Intelligence-a1
Elements of Artificial Intelligence's assignment 1
B551-Artificial-Intelligence-a2
Elements of Artificial Intelligence's assignment2
B551-Artificial-Intelligence-a3
Elements of Artificial Intelligence's Assignment3
B551-Artificial-Intelligence-a4
Elements of Artificial Intelligence's Assignment4
Getting-and-Cleaning-Data-Course-Project
The purpose of this project is to demonstrate one's ability to collect, work with, and clean a data set. The goal is to prepare tidy data that can be used for later analysis. One of the most exciting areas in all of data science right now is wearable computing - see for example this article . Companies like Fitbit, Nike, and Jawbone Up are racing to develop the most advanced algorithms to attract new users. The data linked to from the course website represent data collected from the accelerometers from the Samsung Galaxy S smartphone. A full description is available at the site where the data was obtained: http://archive.ics.uci.edu/ml/datasets/Human+Activity+Recognition+Using+Smartphones Here are the data for the project: https://d396qusza40orc.cloudfront.net/getdata%2Fprojectfiles%2FUCI%20HAR%20Dataset.zip You should create one R script called run_analysis.R that does the following. Merges the training and the test sets to create one data set. Extracts only the measurements on the mean and standard deviation for each measurement. Uses descriptive activity names to name the activities in the data set Appropriately labels the data set with descriptive variable names. Creates a second, independent tidy data set with the average of each variable for each activity and each subject.
nishant07's Repositories
nishant07/Getting-and-Cleaning-Data-Course-Project
The purpose of this project is to demonstrate one's ability to collect, work with, and clean a data set. The goal is to prepare tidy data that can be used for later analysis. One of the most exciting areas in all of data science right now is wearable computing - see for example this article . Companies like Fitbit, Nike, and Jawbone Up are racing to develop the most advanced algorithms to attract new users. The data linked to from the course website represent data collected from the accelerometers from the Samsung Galaxy S smartphone. A full description is available at the site where the data was obtained: http://archive.ics.uci.edu/ml/datasets/Human+Activity+Recognition+Using+Smartphones Here are the data for the project: https://d396qusza40orc.cloudfront.net/getdata%2Fprojectfiles%2FUCI%20HAR%20Dataset.zip You should create one R script called run_analysis.R that does the following. Merges the training and the test sets to create one data set. Extracts only the measurements on the mean and standard deviation for each measurement. Uses descriptive activity names to name the activities in the data set Appropriately labels the data set with descriptive variable names. Creates a second, independent tidy data set with the average of each variable for each activity and each subject.
nishant07/2014
Official content for the Fall 2014 Harvard CS109 Data Science course
nishant07/2014_data
Data directory for the CS109 Data Science course
nishant07/AuthorProfiling
Predict gender and age of author from text
nishant07/awesome-courses
:books: List of awesome university courses for learning Computer Science!
nishant07/awesome-scalability
The Patterns of Scalable, Reliable, and Performant Large-Scale Systems
nishant07/B551-Artificial-Intelligence-a1
Elements of Artificial Intelligence's assignment 1
nishant07/B551-Artificial-Intelligence-a2
Elements of Artificial Intelligence's assignment2
nishant07/B551-Artificial-Intelligence-a3
Elements of Artificial Intelligence's Assignment3
nishant07/B551-Artificial-Intelligence-a4
Elements of Artificial Intelligence's Assignment4
nishant07/B551-Artificial-Intelligence-a5
Elements of Artificial Intelligence's Assignment5
nishant07/B551-Artificial-Intelligence-a6
Elements of Artificial Intelligence's Assignment6
nishant07/cassandra-workshop-series
All materials for the Cassandra Workshop Series in a single place
nishant07/course-builder
nishant07/courses
Course materials for the Data Science Specialization: https://www.coursera.org/specialization/jhudatascience/1
nishant07/CSI_C_Programs
nishant07/datasci_course_materials
Public repository for course materials for the Spring 2013 session of Introduction to Data Science, an online coursera course.
nishant07/django-rest-api
nishant07/ExData_Plotting1
Plotting Assignment 1 for Exploratory Data Analysis
nishant07/h2o-hackathon-2017
nishant07/hackerrank
All hackerrank problems submitted by me
nishant07/InsightDataEngineeringCC17
nishant07/Kaggle_Outbrain-Click-Prediction
https://www.kaggle.com/c/outbrain-click-prediction
nishant07/labs
This is a collection of tutorials for learning how to use Docker with various tools. Contributions welcome.
nishant07/oo_java
https://www.coursera.org/learn/object-oriented-java
nishant07/ProgrammingAssignment2
Repository for Programming Assignment 2 for R Programming on Coursera
nishant07/RepData_PeerAssessment1
Peer Assessment 1 for Reproducible Research
nishant07/RGoogleAnalytics
R Library to easily extract data from the Google Analytics API into R
nishant07/WhatsAPI-Official
The php WhatsApp library
nishant07/Z604-Big-Data-Analytics