MKasigwa

Wunder CorporationKigali, Rwanda

Pinned Repositories

airbnb_seattle_listing_analysis
Datascience nano degree project 1
Language:Jupyter Notebook10
archevie
Language:HTML2 0 00
chandelier
Language:HTML2 1 01
Data-Struture-With-JavaScript
Language:JavaScript2 1 00
disaster_response_pipeline
Disaster response pipeline machine learning
Language:Python10
mk
Language:HTML2 1 00
MKasigwa
2 1 00
portfolio
Language:JavaScript2 1 00
testPython
2 0 00
typeorm-crash-course
Typeorm course
2 1 00

MKasigwa's Repositories

MKasigwa/archevie
Language:HTML2 0 00
MKasigwa/chandelier
Language:HTML2 1 01
MKasigwa/Data-Struture-With-JavaScript
Language:JavaScript2 1 00
MKasigwa/mk
Language:HTML2 1 00
MKasigwa/MKasigwa
2 1 00
MKasigwa/portfolio
Language:JavaScript2 1 00
MKasigwa/testPython
2 0 00
MKasigwa/typeorm-crash-course
Typeorm course
2 1 00
MKasigwa/airbnb_seattle_listing_analysis
Datascience nano degree project 1
Language:Jupyter Notebook10
MKasigwa/disaster_response_pipeline
Disaster response pipeline machine learning
Language:Python10
MKasigwa/recommendation_engines
1
MKasigwa/starbuck_analysis
Language:Jupyter Notebook1
MKasigwa/nkpremices
My Portfolio
0 0 00
MKasigwa/oesukam
Language:Vue0 0 00
MKasigwa/messaging-chat
MKasigwa/nestjs-kafka
Integrate KafkaJS into Nest.js project to produce and consume messages from local kafka server
MKasigwa/pacyL2K19
My readme
MKasigwa/udacity-disaster-response-pipeline
This Project is part of Data Science Nanodegree Program by Udacity in collaboration with Figure Eight. The dataset contains pre-labelled tweet and messages from real-life disaster events. The project aim is to build a Natural Language Processing (NLP) model to categorize messages on a real time basis.