Data science project using Kaggle Datasets and Kernels
Cooking a data science project using Kaggle dataset and kernel We are working together to use fresh materials (data), to prepare them using different tools, and to work together with a delicious result - a published dataset and some quiet analysis that we are sharing with the world. Working with dataset and kernel We will pull public data from the city of Los Angeles open data portal, including environmental health violations from restaurants in Los Angeles. So we will create new datasets using the data, and work together on the kernel before releasing it into the world. In this blog you will learn: How to create a new, private, Kaggal dataset from raw data How to share your dataset before making it public to those involved in your collaboration Adding helpers to private kernels How to use helpers in Koggle kernels Data is most powerful when it is reproducible code and shared with experts and the community at large. By placing data and code on a shared, consistent platform, you get the