A grassroots live tour by YouTuber Louis Rossmann highlights growing resistance to companies that keep people from controlling their devices. The train blasts through right as Louis Rossmann starts to speak. This has happened several times already at the event he's hosting on a Friday night in San Jose, California. All the speakers before him patiently paused when the train on the nearby tracks roared by, its loud horn blaring, then resumed talking. But Rossmann is mid-sentence in his rapid-fire delivery about the topic he's fiercely passionate about, and he doesn't stop. He shouts over the train.

Fulu sets repair bounties on consumer products that employ sneaky features that limit user control. Just this week, it awarded more than $10,000 to the person who hacked the Molekule air purifier. Companies tend to be rather picky about who gets to poke around inside their products. Manufacturers sometimes even take steps that prevent consumers from repairing their device when it breaks, or modifying it with third-party products. But those unsanctioned device modifications have become the raison d'être of a bounty program set up by a nonprofit called Fulu, or Freedom from Unethical Limitations on Users.

They took NYC Data Science Academy 12 week full time Data Science Bootcamp program between Sept 23 to Dec 18, 2015. The post was based on their fourth class project(due at 8th week of the program). As part of a Kaggle competition, we were challenged by Rossmann, the second largest chain of German drug stores, to predict the daily sales for 6 weeks into the future for more than 1,000 stores. Exploratory data analysis revealed several novel features, including spikes in sales prior to, and preceding store refurbishment. We also engineered several novel features by the inclusion of external data including Google Trends, macroeconomic data, as well as weather data.

They took NYC Data Science Academy 12 week full time Data Science Bootcamp program between Sept 23 to Dec 18, 2015. The post was based on their fourth class project(due at 8th week of the program). As part of a Kaggle competition, we were challenged by Rossmann, the second largest chain of German drug stores, to predict the daily sales for 6 weeks into the future for more than 1,000 stores. Exploratory data analysis revealed several novel features, including spikes in sales prior to, and preceding store refurbishment. We also engineered several novel features by the inclusion of external data including Google Trends, macroeconomic data, as well as weather data.