Amine Agrane's Projects
16-bit CPU written in VHDL
Coursera Regression Models Course Project
Course materials for the Data Science Specialization: https://www.coursera.org/specialization/jhudatascience/1
This project implement a simple mediator in java that will integrate and merge different sources of data in the field of cinema.
Code and resources for my blog and articles to share Data Science and AI knowledge and learnings with everyone
The Leek group guide to data sharing
Detectron2 is FAIR's next-generation platform for object detection and segmentation.
This project is a multi-class image classification. I have used TensorFlow `mobilenet_v2_130_224` (https://tfhub.dev/google/imagenet/mobilenet_v2_130_224/classification/4) to build and train a Neural Network that will classify dog breed from images passed as input.
The aim of this project is to design and implement a library allowing to generate and represent finite state machine also know as finite automaton. The library will also implement algorithms to perform operations that are specific to finite state automaton : Determination, Minimization, Complementary, Elimination of ***ε*** transitions, etc
Réduction du nombre de couleurs utilisé dans une image par application de L'algorithme de Floyd-Steinberg.
French word embeddings from series sub-titles
Simple Mastermind game usable in console mode.
Exercise notebooks for Machine Learning modules on Microsoft Learn
Lab files for Azure Machine Learning exercises
OS Project : Simple file manager that uses a simulated partition (UNIX file) as support to store files and directories.
Transforms PDF, Documents and Images into Enriched Structured Data
Code samples from the book Web Scraping with Python http://shop.oreilly.com/product/0636920034391.do
Building pipeline to process the real-time data using Spark and Mongodb.
Segment documents into coherent parts using word embeddings.
The goal of this project is to create a simplified version of "wargame" to be played by 2 players and to implement a low-level artificial intelligence, so that it can play a game and compete with a human player. The Minimax algorithm is then implemented and optimized with the alpha/beta pruning.
This project consists in performing a Topics Modeling as well as a sentiment analysis on user opinions of Android applications. Data is extracted using Web Scrapping from the Google Play Store.
We build a machine learning model to predict if a wine is considered as good or not. The model takes as input some wine characteristics (alcohol content, acidity, etc), and then describes the quality of the wine as (“Good” or “Bad”). We starts with decision tree and then use Random Forest to improve our classification scores.