abhiverma1924/machine-learning.

Algorithms and Fundamentals of Machine learning

#Challenge - Hardwork Pays Off

Hardwork Pays Off

Predicting Exam Scores using Machine Learning

Since you are a CSE student, you are expected to work hard and get better results than others. To track your time and expected performance in the Machine Learning Challenge, Your Mentor has asked to you install walkatime on your device which is an efficient time tracking tool to track your daily coding activity. It measures how much time you have spend on coding daily.

Challenge

In this challenge, your mentor gives you walkatime data of his past students and how they performed in the evaluation exam. Your task is to predict the score you will get given the amount of time you spend on coding daily.

Input You are given one feature corresponding to time noted by walkatime.

Output A scalar denoting the level of perfomance student achived by devoting the given time.

Challenge - Air Pollution

Air Pollution is Rising!

Predicting Pollution Levels using Machine Learning

It is winter time in Delhi so Cody decided to go for a walk to the news stand and on reaching was surprised to see the air quality index of Delhi in the newspaper . So he decided to collect the air samples of different locations and then took these samples to his lab where he extracted five features of the air he collected which can be used to predict the air quality index and combined it with the air quality index given in the newspapers. You are provided with the data collected by Cody and your job is to design a machine learning model which given the features extracted by Cody can predict air quality.

Data consist of three csv files :-

Train.csv
Testcsv

Train:- The train data consists of five feature columns and one target column.All the feature columns are numeric and target value is also numeric.

Test:- test data consist all the columns contained by train with the the exception of target column which u have to predict using the model trained on train data.

Challenge - Diabetes Classification

Diabetes Challenge!

Machine Learning in Health

Diabetes is a condition that impairs the body's ability to process blood glucose, otherwise known as blood sugar. In the United States, the estimated number of people over 18 years of age with diagnosed and undiagnosed diabetes is 30.2 million. The figure represents between 27.9 and 32.7 percent of the population.

Without ongoing, careful management, diabetes can lead to a buildup of sugars in the blood, which can increase the risk of dangerous complications, including stroke and heart disease.

Different kinds of diabetes can occur, and managing the condition depends on the type. Not all forms of diabetes stem from a person being overweight or leading an inactive lifestyle. In fact, some are present from childhood.

Challenge

In this problem you are given a Diabetes Data set consisting of following features -

['Pregnancies', 'Glucose', 'BloodPressure', 'SkinThickness', 'Insulin', 'BMI', 'DiabetesPedigreeFunction', 'Age', 'Outcome']

and your task is to predict whether a person is suffering from diabetes or not (Binary Classification)