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 with Polynomic features
Decision Tree Regression
Random Forest Regression
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 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.
** 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 […]