Chitaranjanpradhan

Air-quality-

The dataset contains 9358 instances of hourly averaged responses from an array of 5 metal oxide chemical sensors embedded in an Air Quality Chemical Multisensor Device. The device was located on the field in a significantly polluted area, at road level,within an Italian city. Data were recorded from March 2004 to February 2005 (one year)representing the longest freely available recordings of on field deployed air quality chemical sensor devices responses. Ground Truth hourly averaged concentrations for CO, Non Metanic Hydrocarbons, Benzene, Total Nitrogen Oxides (NOx) and Nitrogen Dioxide (NO2) and were provided by a co-located reference certified analyzer. Evidences of cross-sensitivities as well as both concept and sensor drifts are present as described in De Vito et al., Sens. And Act. B, Vol. 129,2,2008 (citation required) eventually affecting sensors concentration estimation capabilities. Missing values are tagged with -200 value. This dataset can be used exclusively for research purposes. Commercial purposes are fully excluded.

Book-Recommendation-Engine-using-KNN

dataset contains 1.1 million ratings (scale of 1-10) of 270,000 books by 90,000 users. After importing and cleaning the data, use NearestNeighbors from sklearn.neighbors to develop a model that shows books that are similar to a given book.

bot-

c-

Cat-and-Dog-Image-Classifier

Chitaranjanpradhan

Config files for my GitHub profile.

Coding-Solution

datasciencecoursera

Deep-Learning

h4ck3r

Chitaranjanpradhan/h4ck3r

Chitaranjanpradhan/Air-quality-

The dataset contains 9358 instances of hourly averaged responses from an array of 5 metal oxide chemical sensors embedded in an Air Quality Chemical Multisensor Device. The device was located on the field in a significantly polluted area, at road level,within an Italian city. Data were recorded from March 2004 to February 2005 (one year)representing the longest freely available recordings of on field deployed air quality chemical sensor devices responses. Ground Truth hourly averaged concentrations for CO, Non Metanic Hydrocarbons, Benzene, Total Nitrogen Oxides (NOx) and Nitrogen Dioxide (NO2) and were provided by a co-located reference certified analyzer. Evidences of cross-sensitivities as well as both concept and sensor drifts are present as described in De Vito et al., Sens. And Act. B, Vol. 129,2,2008 (citation required) eventually affecting sensors concentration estimation capabilities. Missing values are tagged with -200 value. This dataset can be used exclusively for research purposes. Commercial purposes are fully excluded.

Chitaranjanpradhan/Book-Recommendation-Engine-using-KNN

dataset contains 1.1 million ratings (scale of 1-10) of 270,000 books by 90,000 users. After importing and cleaning the data, use NearestNeighbors from sklearn.neighbors to develop a model that shows books that are similar to a given book.

Chitaranjanpradhan/bot-

Chitaranjanpradhan/c-

Chitaranjanpradhan/Cat-and-Dog-Image-Classifier

Chitaranjanpradhan/Chitaranjanpradhan

Config files for my GitHub profile.

Chitaranjanpradhan/Coding-Solution

Chitaranjanpradhan/datasciencecoursera

Chitaranjanpradhan/Deep-Learning

Chitaranjanpradhan/Employee-attrition

People are the lifeblood of an organization. Employee attrition is an extremely important and relevant business problem all organizations face. The major problem with high attrition is the cost to the organization and the time and resource investment. We invite you to propose ideas that can help in predicting and finding proactive ways of reducing attrition using technologies of your choice For eg: use available data/ and create modeling tools to predict which employees are more likely to leave given some attributes like absenteeism, stagnation in a role, active disengagement, etc.

Chitaranjanpradhan/Identification-of-Phishing-Websites

Application of Machine learning & Feature Selection techniques for Classification of Phishing Websites

Chitaranjanpradhan/Indian-Premier-League-Cricket-Ball-By-Ball-Cricket-Data

Context Cricket is a bat-and-ball game played between two teams of eleven players each on a cricket field, at the center of which is a rectangular 20-meter (22-yard) pitch with a target at each end called the wicket (a set of three wooden stumps upon which two bails sit). Each phase of play is called an innings, during which one team bats, attempting to score as many runs as possible, whilst their opponents bowl and field, attempting to minimize the number of runs scored. When each innings ends, the teams usually swap roles for the next innings (i.e. the team that previously batted will bowl/field, and vice versa). The teams each bat for one or two innings, depending on the type of match. The winning team is the one that scores the most runs, including any extras, gained (except when the result is not a win/loss result). Source: https://en.wikipedia.org/wiki/Cricket Content All Indian Premier League Cricket matches between 2008 and 2016. This is the ball by ball data of all the IPL cricket matches till season 9. The dataset contains 2 files: deliveries.csv and matches.csv. matches.csv contains details related to the match such as location, contesting teams, umpires, results, etc. deliveries.csv is the ball-by-ball data of all the IPL matches including data of the batting team, batsman, bowler, non-striker, runs scored, etc Inspiration Research scope: Predicting the winner of the next season of IPL based on past data, Visualizations, Perspectives, etc.

Chitaranjanpradhan/IPLIndian-Premier-League-Cricket-Ball-By-Ball-Cricket-Data

Context Cricket is a bat-and-ball game played between two teams of eleven players each on a cricket field, at the center of which is a rectangular 20-meter (22-yard) pitch with a target at each end called the wicket (a set of three wooden stumps upon which two bails sit). Each phase of play is called an innings, during which one team bats, attempting to score as many runs as possible, whilst their opponents bowl and field, attempting to minimize the number of runs scored. When each innings ends, the teams usually swap roles for the next innings (i.e. the team that previously batted will bowl/field, and vice versa). The teams each bat for one or two innings, depending on the type of match. The winning team is the one that scores the most runs, including any extras, gained (except when the result is not a win/loss result). Source: https://en.wikipedia.org/wiki/Cricket Content All Indian Premier League Cricket matches between 2008 and 2016. This is the ball by ball data of all the IPL cricket matches till season 9. The dataset contains 2 files: deliveries.csv and matches.csv. matches.csv contains details related to the match such as location, contesting teams, umpires, results, etc. deliveries.csv is the ball-by-ball data of all the IPL matches including data of the batting team, batsman, bowler, non-striker, runs scored, etc Inspiration Research scope: Predicting the winner of the next season of IPL based on past data, Visualizations, Perspectives, etc.

Chitaranjanpradhan/loan-risk-credit-

Chitaranjanpradhan/Loan-Risk-Prediction-Using-Transaction-Information

Objective of the project is to study the ability of neural network algorithms to handle the problem of predicting credit default that measures the creditworthiness of the loan application over a time period

Chitaranjanpradhan/malarial-mosquito

Chitaranjanpradhan/mask

Chitaranjanpradhan/Peer-graded-Assignment-Getting-and-Cleaning-Data-Course-Project

Peer-graded Assignment: Getting and Cleaning Data Course Project

Chitaranjanpradhan/Rock-Paper-Scissors

ou will create a program to play Rock, Paper, Scissors. A program that picks at random will usually win 50% of the time. To pass this challenge your program must play matches against four different bots, winning at least 60% of the games in each match

Chitaranjanpradhan/stock-monitoring-platform

Chitaranjanpradhan/studytour

In the tech industry it is common knowledge that the current state-of-the-art technology will be outdated in five to ten years. This has made tech the most agile industry. So how can we apply this mindset to other industries as well and encourage people in those industries to develop their knowledge? Key problems How can we ensure everyone is able to educate themselves throughout their lives? How can we make online learning more personalized and optimal? How can we measure the quality and objectivity of learning materials? Target We’re looking for a web app that addresses one or more of these problems. The app could, for example, optimize e-learning, help people continue learning throughout their lives, or measure the quality and objectivity of learning materials.

Chitaranjanpradhan/studytouronline

https://studytour.tadabase.io/edtech#!/default

Chitaranjanpradhan/Voice-to-Text-