annish395 Goto Github PK

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Name: Annish M

Type: User

Bio: Aspiring Data Professional Skilled in data Collecting, Organizing, Interpreting and analyzing data in order to drive successful business solutions.

Location: Chennai

Annish M's Projects

airline-passenger-satisfaction-

At present the reviews from the customers are collected through feedback forums, or links via Email, SMS, or QR Code. And then we predict our customer satisfaction, which is exposed to human errors and a lot of time might be spent in predicting the satisfaction manually. Thus by using a machine learning model we can figure out how the variables help in predicting the customer satisfaction of the airline which saves a lot of time and increases the efficiency.

introduction-to-deep-learning-and-neural-networks

Coursera - Introduction to Deep Learning and Neural Networks with Keras (Offered By IBM)

online-shopping-revenue-using-clustering-and-pca-unsupervised-machine-learning-

Based on given data of visitors browsing for online shopping, build different clusters to know whether person is only browsing and visiting multiples pages or also generating revenue for the shopping websites as well. Analyse and compare the clusters formed with the existing Revenue Column.

parkinson-disease-prediction-using-classification-method-machine-learning-

Build the binomial machine learning model to predict the Parkinson disease. The objective of this model is to classify the patients with the Parkinson disease. Perform the required pre-processing steps prior to model building and evaluate the model performance through proper tuning process.

population-of-u.s.-cities--linear-regression-continuous-variable-

Build a Linear Machine Learning model to understand the relationship between the population of US cities in the year 1920 and 1930. Evaluate the model performance with appropriate measures. Perform all the required graphical and quantitative exploratory data analysis prior to model building. The dataset has 49 rows and 2 columns. The measurements are the population (in 1000's) of 49 U.S. cities in 1920 and 1930. The 49 cities are a random sample taken from the 196 largest cities in U.S

sports-analytics--fifa

A new football club named ‘Brussels United FC’ has just been inaugurated & the team is looking to hire players for their roster. Management wants to make such decisions using data based approach. Player data for all teams has been acquired from FIFA. The data contains details for over 18,000 players playing in various football clubs in Europe. It contains information on age, skill rating, wages and player value, etc. in the files named fifa.csv which is data file and fifa_variable_information.csv

telecom-churn-

In this highly competitive market, the telecommunications industry experiences an average of 15-25% annual churn rate. For many incumbent operators, retaining high profitable customers is the number one business goal. To reduce customer churn, telecom companies need to predict which customers are at high risk of churn. In this project, you will analyze customer-level data of a leading telecom firm, build predictive models to identify customers at high risk of churn.

annish395 Goto Github PK

Annish M's Projects

airline-passenger-satisfaction-

introduction-to-deep-learning-and-neural-networks

online-shopping-revenue-using-clustering-and-pca-unsupervised-machine-learning-

parkinson-disease-prediction-using-classification-method-machine-learning-

population-of-u.s.-cities--linear-regression-continuous-variable-

sports-analytics--fifa

telecom-churn-

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