facebook-pixel

About Me

James Le is a Software Developer with experiences in Product Management and Data Analytics. He played a pivotal role in the operation of a start-up organization at Denison University.

A Friendly Introduction to Open Source Data Science for Business Leaders

Open source is a key enabler for enterprise data science, both in terms of the growing ecosystem of open-source tools and the expanding number of complementary enterprise data science platforms that incorporate and build on open source languages and tools. The challenge is identifying which of those tools is relevant and valuable to your business. Assessing the maturity of these projects, grappling with any licensing issues and making sure your team has the correct skillset to use them are challenges that many companies are now facing.

How to Run an Effective Data Science POC in 7 Steps

A proof of concept (POC) is a popular way for businesses to evaluate the viability of a system, product, or service to ensure it meets specific needs or sets of predefined requirements. What does running a POC mean in practice specifically for data science? When it comes to the evaluation of data science solutions, POCs should prove not just that a solution solves one particular, specific problem, but that a system will provide widespread value to the company: that it’s capable of bringing a data-driven perspective to a range of the business’s strategic objectives.

The 5-Step Recipe to Make Your Deep Learning Models Bug-Free

Deep learning troubleshooting and debugging is really hard. It’s difficult to tell if you have a bug because there are lots of possible sources for the same degradation in performance. Furthermore, the results can be sensitive to small changes in hyper-parameters and dataset makeup. To train bug-free Deep Learning models, we really need to treat building them as an iterative process. To make this process easier and catch errors as early as possible, this article suggests steps you can follow.

The Harvard Innovation Lab

Made in Boston @

The Harvard Innovation Lab

350

Matching Providers

Matching providers 2
comments powered by Disqus.