Ready to learn Machine Learning? Browse courses like Machine Learning Foundations: Supervised Learning developed by industry thought leaders and Experfy in Harvard Innovation Lab. Nothing is worse than AI project failure. Everyone has AI on their 2017/2018 roadmap these days. Bottom-tier innovation verticals like HR, multi-level marketing, entertainment, fashion, medical, supply chain (anyone else we should throw under the bus?) are even starting to talk about it.

This is a guest post from Ben Taylor, co-founder and Chief Data Officer at Ziff.ai. Ben has over 13 years of machine learning experience. He has worked for Intel/Micron, a hedge fund as a quant, and recently helped build out HireVue's (a Sequoia company) data science team and AI product. Ben has filed eight patents ranging from machine learning to nanotechnology, and appreciates the differences between IP and trade secrets. He has hired 5 data scientists and is actively involved in the community.

Everyone has AI on their 2017/2018 roadmap these days. Bottom-tier innovation verticals like HR, multi-level marketing, entertainment, fashion, medical, supply chain (anyone else we should throw under the bus?) are even starting to talk about it. Everyone wants to hire a data scientist. Fortune 1500 companies are throwing out multi-million dollar data leadership positions to lead their data teams to success. Despite the hype and excitement, the majority of companies that commit to tackling AI projects will fail.