Nada's repositories
Amazon-Laptop-Price-Regression
Regression Project for SDAIA T5 Data Science Bootcamp. This project will choose the best regression model to predict laptops prices.
MTA-Cookies-Booth
The purpose of this project is to study and understand the Metropolitan Transportation Authority's MTA data set.
Face-Mask-Detection-DeepLearning
we will build a deep learning model that recognizes persons wearing masks, people with no masks, and people wearing erroneous masks.
IMDB_Reviews_NLP
The goal of this project was to use unsupervised learning to handle the text data which consists of movie reviews and build a classification model. The model should be able to classify the sentiment of the movie reviews, whether it is a positive or negative sentiment.
Bank_Marketing_Classification
The primary goal of the project is to predict whether or not a customer will subscribe to a service offered by the bank.
Iris_Decisiontree_classifier
The Iris flower data set or Fisher's Iris data set is a multivariate data set. The data set consists of 150 samples from each of three species of Iris (Iris setosa-0, Iris virginica-1 and Iris versicolor-2). Four features were measured from each sample: the length and the width of the sepals and petals, in centimeters. Based on the combination of these four features, Fisher developed a linear discriminant model to distinguish the species from each other