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churn-prediction-using-logistic-regression

Prediction of the churn values of the customer by applying the logistic regression algorithm.

coursera-capstone-project

customer-segmentation-using-k-means

Imagine that you have a customer dataset, and you need to apply customer segmentation on this historical data. Customer segmentation is the practice of partitioning a customer base into groups of individuals that have similar characteristics. It is a significant strategy as a business can target these specific groups of customers and effectively allocate marketing resources. For example, one group might contain customers who are high-profit and low-risk, that is, more likely to purchase products, or subscribe for a service. A business task is to retaining those customers. Another group might include customers from non-profit organizations.

deep-learning

Deep Learning Specialization

depression-analysis-using-social-media-twitter-

In this project, I have build a Convolutional Neural Network to predict if the tweets of a certain person are depressive or normal. I have compared the Convolutional Neural Network model with the Logistic Regression Model by finding out the accuracy of both the models. The Convolutional Neural Networks have a better and far more accuracy percentage i.e. 99.79% than the Logistic Regression which has an accuracy percentage of 83.775%.

facial-emotion-classifier

This classifier will predict the emotion from the facial expressions of a person. I have used haar cascade classifier to capture the facial expressions and trained the model using Convolutional Neural Networks.

heart-rate-prediction

invisibility_cloak

This is how you can create your own invisibility cloak.

titanic-data-analysis

The analysis of the death rate and alive people left in the titanic ship accident and the calculation of how many of the alive people were men,women and children.