hibatallahk Goto Github PK

5th-gl-bpg-fifth-generation-language-for-a-business-process-generator

Here is my end of studies Master's project

beta-bank-churn-prediction-supervised-learning

cars_data_preprocess_using_ml

carspredictionml_numedicalmethods

certification_data_scientist_yandex

computervisionpracticum

crankshaft_list_dataanalysis

credit_scoring_data_analysis

Prepare a report for a bank’s loan division. Building a credit score for a potential customer. A credit score is used to evaluate the ability of a potential borrower to repay their loan.

data-analysis-cars-data

data-collection-and-storage-sql-project

data-science-portfolio

My Data Science Portfolio

data-viz-using-r

I collected here the technical exercises for Data viz using R and Shiny that I've worked on during my Master's Degree

datapoisoning_fl

Code for Data Poisoning Attacks Against Federated Learning Systems

dataviz-with-r-shiny

Exam Test of Data Viz module (part of my master degree). Using Shiny/R.

datawarehousing

I will share with you theoretical and technical applications for Data warehousing and BI module

fate

An Industrial Grade Federated Learning Framework

federated

A framework for implementing federated learning

federated-1

A collection of Google research projects related to Federated Learning and Federated Analytics.

federated-learning

Everything about Federated Learning (papers, tutorials, etc.) -- 联邦学习

federated-learning-course

flower

Flower - A Friendly Federated Learning Framework

fruits-classification-practicum-task

gcp-data-engineer-certif-

I will collect here along with you materials I am using for preparing the GCP Data Engineer Certification

genetic_algorithms-resource_allocation

gold-recovery-prediction_ml-project

hibatallahk

image-processing-projects

I worked on those Image processing based projects during my First year when preparing my Master's Degree

insuranceprediction

The Sure Tomorrow insurance company wants to solve several tasks with the help of Machine Learning and you are asked to evaluate that possibility. Task 1: Find customers who are similar to a given customer. This will help the company's agents with marketing. Task 2: Predict whether a new customer is likely to receive an insurance benefit. Can a prediction model do better than a dummy model? Task 3: Predict the number of insurance benefits a new customer is likely to receive using a linear regression model. Task 4: Protect clients' personal data without breaking the model from the previous task. It's necessary to develop a data transformation algorithm that would make it hard to recover personal information if the data fell into the wrong hands. This is called data masking, or data obfuscation. But the data should be protected in such a way that the quality of machine learning models doesn't suffer.

leaf

Leaf: A Benchmark for Federated Settings

machine-leanring-andrew-ng

Machine learning Course/Certif from Stanford Online by Andrew NG on Coursera