A Friendly Introduction to Open Source Data Science for Business Leaders

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.

Technological Trends in 2019 That I Learned from Ascent Conference

Technological Trends in 2019 That I Learned from Ascent Conference

Last week, I attended the Ascent Conference in the Sheraton Hotel New York at Times Square, which is a 2-day conference focused on bringing together senior leaders in the East Coast tech community to learn, collaborate, and build the relationships needed to spearhead meaningful change. I took some detailed notes of the talks/panels that I attended and decided to use this post to share my major takeaways.

Top 10 Practices to Operationalize Your Data Science Projects in the Real World

Top 10 Practices to Operationalize Your Data Science Projects in the Real World

I want to use this post to share the top 10 practices to deploy your machine learning models into production in the real world.

Datacast Episode 20: Managing Data Scientists with Sunanda Parthasarathy

Datacast Episode 20: Managing Data Scientists with Sunanda Parthasarathy

Sunanda Koduvayur Parthasarathy is an Associate Director of Data Science at Wayfair Inc., where she leads a team of data scientists and engineers to build machine learning solutions that lead to a better shopping experience for all Wayfair customers. Prior to this, she was leading data science innovation R&D projects at the ad-tech startup DataXu. Through her career in data science, she has enjoyed bringing quantitative definition and clarity to unwieldy strategic business questions that have led to multiple high-revenue products.

Best Practices for Using Functional Programming in Python

Best Practices for Using Functional Programming in Python

Python is a very versatile, high-level programming language. It has a generous standard library, support for multiple programming paradigms, and a lot of internal transparency. If you choose, you can peek into lower layers of Python and modify them – and even modify the runtime on the fly as the program executes.

Datacast Episode 19: Data Science in South Africa with Tristan Bergh

Datacast Episode 19: Data Science in South Africa with Tristan Bergh

Tristan Bergh is a systems thinker and data scientist living in Cape Town, South Africa. He studied aeronautical engineering before working as an enterprise software engineer. He worked as an architect on AFIS implementations in Southern Africa, moving into middleware for large fin-tech systems. He restarted his system modeling and machine learning consulting services through 2014, delivering predictive analytics models in healthcare and other domains.

Datacast Episode 18: NLP at Crisis Text Line with Ankit Gupta

Datacast Episode 18: NLP at Crisis Text Line with Ankit Gupta

Ankit Gupta is a data scientist at Crisis Text Line, a New York-based not-for-profit tech startup providing 24/7 free text-based crisis support to individuals. At Crisis Text Line, Ankit developed an AI-driven triage system that detects signals of suicidality within the first few messages sent by texters. Using the triage system, the counselors can serve 93% of at-risk texters in under five minutes.

Datacast Episode 17: Computer Vision Research with Genevieve Patterson

Datacast Episode 17: Computer Vision Research with Genevieve Patterson

Genevieve Patterson is the chief scientist at TRASH, a startup that is developing computational filmmaking tools for mobile iphono-graphers. Before that, she was a Postdoctoral Researcher at Microsoft Research New England. Her work is about creating dialog between AI and people. Her interests include video understanding, visual attribute discovery, human-in-the-loop systems, fine-grained object recognition, medical image understanding, and active learning. Genevieve received her Ph.D. from Brown University in 2016 under the direction of James Hays.

Datacast Episode 16: Bayesian Probabilistic Programming with Peadar Coyle

Datacast Episode 16: Bayesian Probabilistic Programming with Peadar Coyle

Peadar Coyle is a Data Scientist and Engineer based in London. He regularly speaks at conferences and has written a book consisting of numerous interviews with Data Scientists throughout the world. He is also a passionate Open-Source evangelist, himself a supporter who has contributed to PyMC3. Most recently, he founded a stealth startup that is working on hyper-personalized audio.