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O`REILLY – Meet the Expert: Thorr Giddings on .NET Modernization Techniques & Tooling on AWS

December 1, 2021

O`REILLY – Meet the Expert Thorr Giddings on Dotnet Modernization Techniques and Tooling on Aws-iLLiTERATE
English | Size: 590.92 MB
Category: Tutorial

To take full advantage of cloud economics, organizations are modernizing their Windows workloads using a combination of rehosting, replatforming, and refactoring approaches.

O’Reilly – Meet the Expert How Ai Will Change Our World by 2041 With Kai-fu Lee and Tim O’Reilly

October 27, 2021

O’Reilly – Meet the Expert How Ai Will Change Our World by 2041 With Kai-fu Lee and Tim O’Reilly –iLLiTERATE
English | Size: 903.09 MB
Category: Tutorial

AI is poised to enter into our daily lives on a much bigger scale than ever before, touching everything from education to medicine to entertainment.

O’Reilly – Meet the Expert Alexandra Damsker on Building the Future of Fintech With Decentralized Finance

October 25, 2021

O’Reilly – Meet the Expert Alexandra Damsker on Building the Future of Fintech With Decentralized Finance-iLLiTERATE
English | Size: 747.56 MB
Category: Tutorial

Already a rapidly growing field in fintech, decentralized finance (DeFi) has exploded in the last year, growing from a market cap of $700 million in December 2019 to $100 billion as of April 29, 2021.

O’Reilly – Meet the Expert: JJ Asghar on Migrating a Monolith to Cloud Native

October 21, 2021

O’Reilly – Meet the Expert: JJ Asghar on Migrating a Monolith to Cloud Native -iLLiTERATE
English | Size: 681.94 MB
Category: Tutorial

Sponsored by IBM
Moving to a cloud native ecosystem offers many benefits, from cost savings to scalability.

O’Reilly – Meet the Expert Wes Mckinney on Scalable Python You Can Afford

September 7, 2021

O’Reilly – Meet the Expert Wes Mckinney on Scalable Python You Can Afford-iLLiTERATE
English | Size: 896.48 MB
Category: Python

Join us for this edition of Meet the Expert with Apache Arrow cocreator Wes McKinney to learn considerations and best practices for distributed Python at scale-in a cost-effective way.