Monthly Challenge – Sofia Air – Solution – Lone Fighter
SofiaAirRMarkdown2
Tag: Machine Learning
Monthly Challenge – Sofia Air – Solution – Jacob Avila
Preliminary Analisys Due to the objective focused on predicting air quality forecast for the next 24 hours per station, first step should be data understanding for citizen science air quality measurements to group it by station and summarize them by day. To complete this task for inspection and pre-processing in order to find missing data, outliers and […]
Datathon Air Sofia Solution – Team Teljapenosss
— Team Teljapenosss Team Members — Jalapeno (Nasiba Zokirova) Team Mentor: petya-par Business Understanding The levels of air pollution allegedly caused by solid fuel heating and motor vehicle traffic are ever growing in the City of Sofia. The primary economical impact for the City of Sofia was a ruling by the European Court of […]
Datathon Sofia Air Mentors’ Guidelines – On IOT Prediction
In this article the mentors give some preliminary guidelines, advice and suggestions to the participants for the case. Every mentor should write their name and chat name in the beginning of their texts, so that there are no mix-ups with the other menthors. By rules it is essential to follow CRISP-DM methodology (http://www.sv-europe.com/crisp-dm-methodology/). The DSS […]
Datathon Kaufland Mentors’ Guidelines – On Predictive Maintenance
In this article, the mentors give some preliminary guidelines, advice, and suggestions to the participants for the case. Every mentor should write their name and chat name at the beginning of their texts so that there are no mix-ups with the other mentors. By rules, it is essential to follow CRISP-DM methodology (http://www.sv-europe.com/crisp-dm-methodology/). The DSS […]
The Kaufland Case [Global Datathon 2018] – Guidelines by Simon Stiebellehner
The Kaufland Case poses an interesting Predictive Maintenance challenge. First, make sure that you understand what the goals and deliverables are. This is perhaps the most important step in the entire Data Science process. It’s crucial for the business value of the result and it ensures that you spend the little time you have on […]
Using Machine Learning to explain and predict the life expectancy of different countries
The project tries to create a model based on data provided by the World Health Organization (WHO) to evaluate the life expectancy for different countries in years. The data offers a timeframe from 2000 to 2015. The data originates from here: https://www.kaggle.com/kumarajarshi/life-expectancy-who/data The output algorithms have been used to test if they can maintain their accuracy in predicting the life expectancy for data they haven’t been trained. Four algorithms have been used:
Linear Regression
Ridge Regression
Lasso Regression
ElasticNet Regression
Linear Regression with Polynomic features
Decision Tree Regression
Random Forest Regression
An Introduction to Machine Learning Theory and Its Applications: A Visual Tutorial with Examples
What actually does Machine Learning mean and what types of problems does it solve? This Machine Learning tutorial introduces the basics of ML theory, laying down the common themes and concepts. The practical examples substituted with the mathematical functions of univariate linear regression, linear least squares and others make it easy to follow the logic and get comfortable with machine learning basics.
Cryptocurrencies forecasting
Cryptocurrencies are a type of digital currencies that, since their creation, have become a global phenomenon known to most people. Our job is to build a machine learning algorithm able to forecast their price based on a set of given features such as that currency’s price, market cap, circulating supply etc.
Skyscanner: Data Science Challenges in Travel
** We will be streaming live at: https://youtu.be/gm8YdU1iIOw In the middle of the summer the hottest topic is getting away from the city hectic for a short break. There is no better time than this to invite Skyscanner to join us for a great meetup dedicated to meta-search engines for travel and more specifically for flights! Topic: Data Science Challenges in Travel […]