When you hear about a conference rebranded as Big Things, several different scenarios likely cross your mind. Just about everything fits in the Big Things box… However, once you step foot into the conference, with the largest cinema in the world playing host, you immediately know what it is all about.
When surfing the internet, it is quite easy to find sites comparing the most popular Machine learning toolkits (datascience.stackexchange.com, oreilly.com or udacity.com ). These sites give you a lot of information about the strengths and weaknesses of the libraries, how they work and some examples to compare how easy it is to use these types of tools. Therefore, if you are new to the business, they are very helpful for finding the right library to begin to study your data. Actually, they are written by Data Scientists for Data Scientists.
However, as a Software Engineer you would rather know if these tools are going to work well or just crash your servers. Based on this premise, the main objective of this article is to explore some Machine learning libraries and see how they work in a real time semi-production scenario.