About Me


Engineer passionate about technology and their application, doing his part in the machine uprising

On a warpath to become a kaggle expert

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My Portfolio

Some of my stuff and experimentations I have been doing in the fieds of AI, scripting and automation


Machine Learning Python Wikipedia NLP Beautiful Soup

Automatic NLP classifier

How I learned to stop worry and let the script do the heavy work, December 13, 2019

The internet is great, we can actually find information about any subject. The difficult part is then to organize them and classify those data in the right bucket given the topic you are interested in. A classical approach would be to go through everything, read it, store the topic you extracted somewhere somehow (in your head, post-it, csv file…), and then classify manually all those documents in the right bucket. It can be somehow ok if your corpus is not too big, but once you reach a dozen documents whose length may vary a lot, it becomes quite a burden. Moreover, you may be interested in only one of the topic covered in the document and would still have to read the whole bunch and your classification may not be consistent. Surely there is a better way to use our time…


Python AutoML Features Selection Features ENgineering Evolutionnary algorithm

My Take at AutoML, March 15, 2020

How I learned to stop worry and let the script do the heavy work

Machine learning is great but it is also a difficult and somewhat cryptic task and can be hard to democratize. On the other hand, even taking into account the no free lunch theorem, there are some techniques and process to automate the creation of optimized models. This article presents easyML a script for automation of features selection, features engineering and training of a model.


Python Data analysis APIs Data vizualisation Geek

Gotta compute them all, May 12, 2020

Or how to play pokemon the right way

Recently, a fellow data enthusiast, https://towardsdatascience.com/@anis.ayari shared a tutorial on data visualization using the kaggle pokemon dataset. This made me wonder if there is a way to beat the game using some basic data analysis. I’ll present an analysis of the dataset for the version red and blue, which is the best starter and whether or not Ash actually stood a chance.


Python Deepfakes Autoencoder Programming Image Processing

50 layers of autoencoder P1, May 25, 2020

Or how to detect deepfake with autoencoders

Deepfake consist in switching ones face in a video or picture for someones’ else face in the same picture in the best way possible. Advanced techniques based on deep learning and specifically auto-encoders along with the ease of access to computing power and image data enable the creation of very powerful models resulting in fake pictures that are hard to discriminate from real pictures. In this article, I’ll expose some of my experiments based on autoencoder for deepfake detection.


Python finance APIs Automation Data Processing

The python of Wall Street, January 1. 2021

Or how to use python to automate finance


Python OCR Computer Vision Geek Image Processing

Learning to speak pykts, January 1. 2021

Or how to create your custom Optical Characters Recognition (OCR) system

How to create your custom Optical Characters Recognition (OCR) system using python and computer vision. Based on the latest edition of Strange Adventures by DC comics, I realised that an allien language used there could be used for OCR.

An Engineer Journey

Journalling about different Projects That I have been working on, how I implemented it and what I learned on the way