Anatomy of a Data Analytics MVP - Ken Hu

Anatomy of a Data Analytics MVP

Ken Hu /英語

Behind the glamour of mobile apps, business SaaS products have been steadily building itself into a billion dollar industry. With companies such as Salesforce spearheading the adaption of business SaaS products in corporate, startups are rising to take on the SME market. With hot topics such as "big data" and "machine learning" flying around, it may seem overwhelming to put an idea into action. I will walk through the process of building an data analytics minimum viable product (MVP). Attendees will have hands on experiences with the free and/or affordable technology and services that can get their MVP up and running. This talk assumes attendees understand the basic of Python. Basic understanding of MapReduce and NoSQL databases will be big pluses as well.


Profile picture
I am a data scientist, software developer, and aspiring entrepreneur. I'm especially interested in machine learning, information retrieval, text analytics, and cloud technology. My weapon of choice is Python. I previously founded a social data analysis company and developed its core technology. I grew the startup into a profitable entity, without any outside funding.


text analytics, machine learning, information retrieval, startup






Applied AI


Data Scientist

HDE, Inc. mongodb Google

Tagtoo Vpon Github Github Github

Quanta Research Institute

AcoMo Technology

CLBC KKTIX QSearch Python Software Foundation Open Source Software Foundry LIVEhouse.in Young Optics Wolf Tea

QSearch Business Next Vpon Inside 硬塞的 DIGITIMES INNOMAMBO 創新曼波

Built with Django and Mezzanine by PyCon Taiwan

Hosting provided by StreetVoice.

網站問題或建議請 回饋給我們