In this krenel we can explore everyhting related to time series forecasting using R. This project will be extensive but really useful for the community to learn about all the different parametersthat compose the time series forecasting.
This is a comprehensive Exploratory Data Analysis for the Personalized Medicine: Redefining Cancer Treatment challenge.It will be using ggplot2 and the tidyverse tools to study and visualise the structures in the data. We have been challenged to automatically classify genetic mutations that contribute to cancer tumor growth (so-called “drivers”) in the presence of mutations that are don’t affect the tumors (“passengers”).
In today’s busy world, finding and dating a romantic partner seems more time consuming than ever. As a result, many people have turned to speed dating as a solution that allows one to meet and interact with a large number of potential partners in a short amount of time. In this report, we want to explore what people are looking for in their speed dating matches, what it takes to become successful in getting approvals from a potential partner, if there exist any gender differences, and if any other factors (such as the order you met your partner) influence peoples’ decisions. Finally, we’d like to determine if people really know what they want by comparing their self-reported answers to what actually influences peoples’ decisions.
This analysis contains EDA, graphs, NLP preprocessing, lexicons, graphs and networks, TF-IDFs and WordClouds.
We can mine ‘real’ social media data, and choose the dataset that contains all Tweets in which Hillary Clinton and/or Donald Trump were involved during the 2016 US presidential election campaigns. After a brief overall data exploration , it quickly moved on to mining the Tweet texts themselve.