Pinned Repositories
emines_ts
Times series analysis
Datacamp-project
This project is a classification challenge that aims at building investment strategies on cryptocurrencies based on sentiment extracted from news and social networks. The project was proposed by Napoleon Crypto NaPoleonX, a company specialised in designing quantitative investment solutions, i.e. investment solutions based on algorithms.
deploy-mlm-flask-heroku
Deploy a ML model with Flask to Heroku
emines_ts
Times series analysis
github-assignment
ml-engineer-capstone
Capstone project for Udacity's Machine Learning Engineer nanodegree
NLP_Tasks
NLP notebooks featuring : Sentiment Analysis, Language models, Attention concept
Number-of-Flight-Passengers-Prediction
The goal of the challenge is to predict the number of passengers per plane on some flights in the US. The data is provided to us by a single company. This is a supervised regression problem. From the company point of view, the interest of this challenge is to be able to evaluate the percentage of no-show reservations, in order to properly calibrate overbooking. Some passengers make reservation but do not show up on the flight, leading to empty seats in the plane. Estimating the number of passengers effectively boarding the plane is thus important for the company. The left-out data has dates that come after the training data, so a time series approach is possible.
UNSUPERVISED-MACHINE-LEARNING
ONIVIA
Duffany's Repositories
Duffany/Datacamp-project
This project is a classification challenge that aims at building investment strategies on cryptocurrencies based on sentiment extracted from news and social networks. The project was proposed by Napoleon Crypto NaPoleonX, a company specialised in designing quantitative investment solutions, i.e. investment solutions based on algorithms.
Duffany/deploy-mlm-flask-heroku
Deploy a ML model with Flask to Heroku
Duffany/emines_ts
Times series analysis
Duffany/github-assignment
Duffany/ml-engineer-capstone
Capstone project for Udacity's Machine Learning Engineer nanodegree
Duffany/NLP_Tasks
NLP notebooks featuring : Sentiment Analysis, Language models, Attention concept
Duffany/Number-of-Flight-Passengers-Prediction
The goal of the challenge is to predict the number of passengers per plane on some flights in the US. The data is provided to us by a single company. This is a supervised regression problem. From the company point of view, the interest of this challenge is to be able to evaluate the percentage of no-show reservations, in order to properly calibrate overbooking. Some passengers make reservation but do not show up on the flight, leading to empty seats in the plane. Estimating the number of passengers effectively boarding the plane is thus important for the company. The left-out data has dates that come after the training data, so a time series approach is possible.
Duffany/UNSUPERVISED-MACHINE-LEARNING