Mandieng's Projects
A curated list of awesome Machine Learning frameworks, libraries and software.
A curated list of awesome Python frameworks, libraries, software and resources
This repo is a work in progress, building a Speech corpus for Berom, a low Resource language in Plateau State Nigeria
A team of data science enthusiasts working on a project on hospitality industry.
:mortar_board: Path to a free self-taught education in Computer Science!
Cat/Dog detection using CNN
Collection of useful data science topics along with code and articles
WeRate Dogs Twitter Data Analysis
Udacity's Diamonds Prediction Project in Python
an exploratory Data Analysis of the Esy Visa Data set
this repo is for an eda watch me do it video
FBI Gun Data and US Census Data are both independent datasets that will be investigated.
An ERC-20 Token Deployed on the BSC and KCC testnet
Labs and demos for courses for GCP Training (http://cloud.google.com/training).
GFPGAN aims at developing Practical Algorithms for Real-world Face Restoration.
A robot powered training repository :robot:
Lab Materials for MIT 6.S191: Introduction to Deep Learning
Aspiring Data Scientist | Applied ML engineer
12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
A repository to index and organize the latest machine learning courses found on YouTube.
MLOps course from DataTalks.Club
This repository is build in association with our position paper on "Multimodality for NLP-Centered Applications: Resources, Advances and Frontiers". As a part of this release we share the information about recent multimodal datasets which are available for research purposes. We found that although 100+ multimodal language resources are available
NLP learning Series
Natural Language Processing Tutorial for Deep Learning Researchers
This Rep attempts to explore and analyse the PISA Global Education dataset. Due to the large volumn of the dataset, this repo zooms in on a sample of the real Data, and further narrows down to a few featues which we explore in the notebook
This repo attempts to utilise two powerful ensemble models, Random forest and Gradient Boosting to Predict the failure patterns of wind energy machinery