Connect. Collect. Normalize. Analyze. An interview with the people from Railz AI (Ep. 189)

In this episode I am with Pasha Zavari - Director of Data Science and Derek Manuge - Co-founder and CTO at Railz. Railz is a very interesting company with an incredible mission: normalizing and extracting insights from the most tedious data out there, financial data.Guess what technology stack are they on? Enjoy the show!   This episode is brought to you by RailzAI The Railz API connects to major accounting platforms to provide you with quick access to normalized and analyzed financial data.   Sponsored by NordVPN NordVPN protects your privacy while you are online. Get secure and private access to the internet by surfing nordvpn.com/DATASCIENCE or use coupon code DATASCIENCE and get a massive discount.   and by Amethix Technologies Amethix use advanced Artificial Intelligence and Machine Learning to build data platforms and predictive engines in domain like finance, healthcare, pharmaceuticals, logistics, energy. Amethix provide solutions to collect and secure data with higher transparency and disintermediation, and build the statistical models that will support your business.   References Railz Homepage: https://go.railz.ai/Railz-DSH Railz API Document: https://go.railz.ai/RailzAPI-DSH Railz API Signup: https://go.railz.ai/RailzSignup-DSH Railz Startup Pricing: https://go.railz.ai/RailzStartupPricing-DSH Railz Careers: https://secure.collage.co/jobs/railz 

How to reinvent banking and finance with data and technology (Ep. 139)

The financial system is changing. It is becoming more efficient and integrated with many more services making our life more... digital. Is the old banking system doomed to fail? Or will it just be disrupted by the smaller players of the fintech industry?In this episode we answer some of these fundamental questions with Alessandro E. Hatami from Pacemakers Subscribe to the Newsletter and come chat with us on the official Discord channel   Our Sponsors This episode is supported by Chapman’s Schmid College of Science and Technology, where master’s and PhD students join in cutting-edge research as they prepare to take the next big leap in their professional journey.To learn more about the innovative tools and collaborative approach that distinguish the Chapman program in Computational and Data Sciences, visit chapman.edu/datascience   Amethix use advanced Artificial Intelligence and Machine Learning to build data platforms and predictive engines in domain like finance, healthcare, pharmaceuticals, logistics, energy. Amethix provide solutions to collect and secure data with higher transparency and disintermediation, and build the statistical models that will support your business.    

Bridging the gap between data science and data engineering: metrics (Ep. 95)

Data science and data engineering are usually two different departments in organisations. Bridging the gap between the two is essential to success. Many times the brilliant applications created by data scientists don't find a match in production, just because they are not production-ready. In this episode I have a talk with Daan Gerits, co-founder and CTO at Pryml.io  

A big welcome to Pryml: faster machine learning applications to production (Ep. 94)

Why so much silence? Building a company! That's why :) I am building pryml, a platform that allows data scientists build their applications on data they cannot get access to. This is the first of a series of episodes in which I will speak about the technology and the challenges we are facing while we build it.  Happy listening and stay tuned!

Episode 68: AI and the future of banking with Chris Skinner [RB]

In this episode I have a wonderful conversation with Chris Skinner. Chris and I recently got in touch at The banking scene 2019, fintech conference recently held in Brussels. During that conference he talked as a real trouble maker - that’s how he defines himself - saying that “People are not educated with loans, credit, money” and that “Banks are failing at digital”. After I got my hands on his last book Digital Human, I invited him to the show to ask him a few questions about innovation, regulation and technology in finance.

Episode 63: Financial time series and machine learning

In this episode I speak to Alexandr Honchar, data scientist and owner of blog https://medium.com/@alexrachnogAlexandr has written very interesting posts about time series analysis for financial data. His blog is in my personal list of best tutorial blogs. We discuss about financial time series and machine learning, what makes predicting the price of stocks a very challenging task and why machine learning might not be enough.As usual, I ask Alexandr how he sees machine learning in the next 10 years. His answer - in my opinion quite futuristic - makes perfect sense.  You can contact Alexandr on Twitter https://twitter.com/AlexRachnog Facebook https://www.facebook.com/rachnog Medium https://medium.com/@alexrachnog   Enjoy the show!  

Episode 62: AI and the future of banking with Chris Skinner

In this episode I have a wonderful conversation with Chris Skinner. Chris and I recently got in touch at The banking scene 2019, fintech conference recently held in Brussels. During that conference he talked as a real trouble maker - that’s how he defines himself - saying that “People are not educated with loans, credit, money” and that “Banks are failing at digital”. After I got my hands on his last book Digital Human, I invited him to the show to ask him a few questions about innovation, regulation and technology in finance.