Name: Salomon Kabongo
Type: User
Company: University of Hannover, L3S and TIB
Bio: My research interests include but not limited to :
-Natural Language Processing,
Automatic Speech Translation and Computer Vision.
https://skabongo.github.
Twitter: SalomonKabongo
Location: Bloomington, USA
Blog: https://skabongo.github.io/
Salomon Kabongo's Projects
AIMS 2020, class on Visual Recognition
Lectures and tutorials for the Deep Natural Language Processing class of the African Master's in Machine Intelligence given by Antoine Bordes
This repository contains, codes of the AMMI Deep Learning Study group
NLP practical Materials of the AMMI course given by Édouard Grave and Kyunghyun Cho(NYU) from Facebook AI
AMMI course on Speech Recognition, given by Gabriel Synnaeve, Neil Zeghidour, Laurent Besacier and Emmanuel Dupoux
My personal website
Udacity's Artificial Intelligence Nanodegree + Specializations (CV and NLP)
Code to train Automatic Speech-to-Text (AST) models
Tools for extracting tables and results from Machine Learning papers
Deep Learning Indaba applications and selection web-app.
How to do Bayesian statistical modelling using numpy and PyMC3
In this project, you'll build your a simple neural network and use it to predict daily bike rental ridership.
Tensorflow implementation of contextualized word representations from bi-directional language models
Classify pictures of cassava leaves into 1 of 4 disease categories (or healthy)
Create an algorithm to distinguish dogs from cats
AIMS-Ghana Assignment on writing an algorithm to classify whether images contain either a dog or a cat.
In this project, we will build a pipeline to process real-world, user-supplied images. Given an image of a dog, my algorithm will identify an estimate of the canine’s breed. If supplied an image of a human, the code will identify the resembling dog breed.
Connect to Google Colab using SSH
SSH into Colab notebook with access to your google drive.
This repository contains parallel corpus for Congolese local languages
A Code-First Introduction to NLP course
Combatting Misinformation using Natural Language Processing (NLP)
My own Experience of the crash course provided by google at https://developers.google.com/machine-learning/crash-course/
Books with Jupyter notebooks
This project reproduces the book Dive Into Deep Learning (www.d2l.ai), adapting the code from MXNet into PyTorch.