Kareemad-10/IATermProject_2019

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Created almost 5 years ago
Updated almost 5 years ago

Kareemad-10/IATermProject_2019

Kareemad-10

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breast_cancer_classification

In this project, we aim to build a classification model that can discriminate between the malignant and benign cancer based on the given characteristics for each type.

Jupyter Notebook

churn_rate

This is a binary classification ML problem, in which we aim to use customers' data related to a certain bank to predict if that customer will churn or not based on multiple given attributes related with that customer.

Jupyter Notebook

task02_ML

In this project, we started to deal with the classification problems by building an efficient classifier to predict the mnist_758 hand-written dataset examples.

Jupyter Notebook

egyptFWD-Project1-BikeShare

In this project within egypt FWD Data Analysis Professional program from Udacity, I aim to perform some data analysis processes in python for the BikeShare company data to improve their profits and performance in the company through some investigations in this real life data/situation for gaining hands-on experience in data analysis using python and it's essential libraries.

egyptFWD-Project2-WeRateDogs

In this project, we aim to perform some data analysis processes based on the collected data from the WeRateDogs Twittter account about dog breeds on the account with the most interesting rates and high or low reviews from the account participants on twitter as well as some interesting data that were well prepared from Udacity team about the project that are stored on Udacity servers that we need to download this data from Udacity servers programmatically to start our data analysis processes and data wrangling steps as well to achieve reach and useful insights from this data

Jupyter Notebook

task01_ML

In this ML project our aim is to build a predictive regression model to predict the median house value for california districts based on multiple attributes related with each district

Jupyter Notebook

boston_task

In this project, I aimed to build an efficient predictive regression model to predict the median house value for Boston in USA based on another important features related with each residential block included in the boston.csv file dataset

Jupyter Notebook