Apriori Algorithm Write a program to generate all association rules whose support is greater than a user-supplied minimum support and whose confidence is greater than a user supplied minimum confidence using Python.

Decision Tree Implement a decision tree-based classifier to predict whether a person’s income is more than $50k or not. The project consists of multiple components that involve data preprocessing, implementing a classification model, assessing the performance of the classifier with the different stopping criteria, and analyzing some of the models that were estimated using Python.

Conceptual & Relational Schema Design a database & implement queries in sql for an online assignment management system.

• Design a Conceptual Schema
• Convert the conceptual schema you designed to a Relational Schema.
• Implement queries

PinnerSage: Multi-Modal User Embedding Framework for Recommendations at Pinterest

Convolutional Neural Network Project Implement a CNN for fashion Classification using Python.

• LeNet-5
• VGG

Transport Level Security

• Background
• TLS
• TLS Architecture
• TLS Concept
• TLS Handshake
• Case

Understanding Hurricane Evacuation Decision Consistency during a Pandemic The dataset collects the information from a survey made in Florida from September to November 2020 that helps to understand hurricane evacuation Decision Consistency during a Pandemic. In this survey respondents were first asked whether they evacuated during hurricane Irma or not and also asked what their evacuation decision for a hypothetical hurricane in presence of a pandemic will be. As no hurricanes hit Florida during the year 2020, the survey considered a hypothetical hurricane to understand decision consistency using R.

PROFESSOR’S SALARY PREDICTION

• Exploratory Analysis
• Exploratory Modeling
• Predicting Modeling
• Conclusions

Striving for Happiness: Multidimensional Analysis of the Factors Impacting Well-Being is a study that aims to identify the factors impacting happiness, well-being, and prosperity in order to help the unhappiest countries focus their efforts to enhance their well-being. Two main datasets are used: The World Happiness Report (WHR) and the Legatum Prosperity Index (LPI). Both data sets consider a wide range of factors to measure happiness and well-being, including GDP per capita, healthy life expectancy, social support, freedom to make choices, generosity, and perceptions of corruption, safety and security, personal freedom, governance, social capital, investment environment, enterprise conditions, infrastructure and market access, economic quality, living conditions, health, education, and natural environment. Hence, even though happiness is subjective and many people in an unhappy country may be happy, and vice-versa, this study considers that these two datasets have a fair way of measuring happiness, prosperity, and well-being.

Using Perceptron and Adaline algorithms to implement a vowel detector in Python The following project is about creating a detector of vowels (A and E) by using Perceptron and Adaline, which are algorithms used for supervised learning of binary classifiers. Both enable neurons to learn and process inputs in the training set one at a time. In this project we will use only a single layer

Using Perceptron and Adaline algorithms to implement a vowel detector in Python The following project is about creating a detector of vowels (A and E) by using Perceptron and Adaline, which are algorithms used for supervised learning of binary classifiers. Both enable neurons to learn and process inputs in the training set one at a time. In this project we will use only a single layer

Using Multi-Layer Perceptron with Backpropagation and Momentum to classify features from Electrocardiogram Dataset. The following project is about implementing a 1 hidden Multilayer Perceptron with Backpropagation and Momentum to classify vectors with features from Electrocardiogram into “Healthy” or “Myocardial Infraction”. This neural network consists of an input layer, a hidden layer, and an output layer.