Samer Kharboush's repositories
ECG
Overview The ECG heartbeat classification model is trained on the MIT-BIH Arrhythmia Database, which contains ECG recordings with annotations for different types of arrhythmias. The model uses a combination of feature extraction with scikit-learn and deep learning with Keras to classify each heartbeat into one of five classes:
Antibiotic-DNA-resistant-sequence
In this project, you’ll have a machine learning model for predicting antibiotic resistance in bacteria. I will be focussing on a species called Neisseria gonorrhoeae, the bacteria which cause gonorrhoea. Gonorrhoea is the second most common sexually transmitted infection (STI) in Europe, after chlamydia. Rates of gonorrhoea infection
AgentGPT
🤖 Assemble, configure, and deploy autonomous AI Agents in your browser.
amazonsales
Amazon data analysis of sales data using sql and Power bi
Auto-GPT
An experimental open-source attempt to make GPT-4 fully autonomous.
Biological-Sequence
Bioinformatics Notebook Basics & Biopython in the field of Bioinformatics and interested in getting initiated into some basic foundational code with fair knowledge you'll find all of these notebooks incredibly useful and great to use as starters.
CAD
What is coronary artery disease? Coronary artery disease (CAD) is the most common type of heart disease in the United States. It is sometimes called coronary heart disease or ischemic heart disease.The main challenges are dangerous side effects and high angiography costs. Today, the development of artificial intelligence-based methods is a valuable
Disease-diagnosing-Prediction
using machine learning different alghorithms to predict disease and interact with gui TKinter APP
Single-Cell-RNA-seq-Feyn-Project
ScRNA can be analyzed using machine learning to improve the performance of quantitative scRNA in future cancer treatment., it can discover new insights about your data and find hidden patterns that you didn't see before. it can identify outliers, detect anomalies, and uncover connections between various components of your data, also Feyn Model
TCGA-OMICS-
Machine learning model for breast cancer severity prediction
ds_salary_proj
this is a testing repo for the datascience salary project from milano
insurace-gan
Calvin-risk showcase
Insurance-Cost-Prediction
This is a machine learning project to predict healthcare insurance charges for individuals based on various features such as age, gender, BMI, smoking habit, and region. The goal is to build a regression model that can accurately predict the insurance charges for new individuals based on their features.
single-cell-RNA
ScRNA can be analyzed using machine learning to improve the performance of quantitative scRNA in future cancer treatment., it can discover new insights about your data and find hidden patterns that you didn't see before. it can identify outliers, detect anomalies, and uncover connections between various components of your data.