Hello, i’m

Ahmed BESBES

1   class Person {

2         constructor() {

3             this.name = "Ahmed BESBES";

4             this.skills = ["Machine Learning", "Software", "DevOps"];

6         }

7   }

Things I do

Machine Learning

+5 years of experience in training models for various usecases

Software Engineering

I craft and build apps to integrate machine learning models

DevOps

I solve your data science problems with scalable and robust solutions

About Me

Hello there!
My name is Ahmed, I'm a data scientist and my goal with this blog is to share with you programming tips, machine learning tutorials, software applications I built and everything data-related to make your life easier.

I'm passionate about neat design and automation and I'm always looking for ideas to build and prototype. If you share the same passion, feel free to reach out.

My Skillsets

PyTorch

Tensorflow

ReactJS

Python

Docker

MongoDB

ElasticSearch

Kibana

Amazon Web Services

Side Projects

Better track your ML experiments with MLflow

Learn how to use MLflow to track your machine learning experiments and make them reproducible

Scrape Twitter Without Limits Using Twint

Learn how to use the Twint package to scrape tweets without any rate limit

How and I built and scaled Cartoonify

In this Youtube video series, I will show how to build and deploy a fun machine learning app to turn your pictures into cartoons. I'll through GANs, serverless architectures, building an interface in React and deploying it to Netlify.

More Demo

Introduction to data scraping in Python with BeautifulSoup and Requests 🚀

This is an introduction to data scraping using Python. For those of you who always wanted to learn how to scrape data for any particular reason, this is the place to start.

Corona Papers: An AI-Powered Search Engine to Explore Covid-19 Research 🚀

In this post, I modestly bring my piece to the building and propose an AI-powered tool to help medical practitioners keep track of the latest research around COVID-19.

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End to end machine learning: from data collection to deployment 🚀

Learn how to build and deploy a machine learning application from scratch: an end-to-end tutorial to learn scraping, training a character level CNN for text classification, buidling an interactive responsive web app with Dash and Docker and deploying to AWS. You're in for a treat !

More Demo

Deep learning for knee injury diagnosis

This repository contains an implementation of a convolutional neural network that classifies specific knee injuries from MRI exams. Check it if you want to learn more or to adapt the code to another medical imaging problem.

More Demo

Character Level CNN

You'll find here a PyTorch implementation of a character level CNN for text classification by Zhang and Lecun (2015) and a video tutorial (by me) accompanying it.

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Neural Networks from Scratch

Learn how to build and train a neural network from scratch. In pure Python only with no frameworks involved. This script helps you start this project.

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Image Dataset Builder

This is a script to help you quickly build custom computer vision datasets for object classification, detection or segmentation. It relies on google_images_download package that scrapes images for each class you define.

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Real-time Style Transfer

A fun application of computer vision on how to mix the style of a painting (say the Starry Night of Van Gogh) and the content of the photograph. Model trained using PyTorch and app built with html and jQuery.

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Image Captioning

How to translate an image to text with the ability to interpret what the machine learning algorithm sees? This is possible using neural networks and specifically encoder-decoders with attention mechanisms.

More Demo

Get In Touch

Thank You

Do You Have Any Queries?