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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