2 great benefits of Python generators (and how they changed me forever)
Learn how to elegantly encapsulate and efficiently scale with Python generators.
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Chris Eng on the challenges of improved application security
The O’Reilly Security Podcast: Vulnerabilities in assembled software and the need for immediate developer feedback.
Introduction to OKRs
Objectives and Key Results (OKRs) have helped organizations like Google and LinkedIn achieve their goals. Learn what OKRs are and how to apply them to your business.
Accelerating Spark workloads using GPUs
Transparent matching of Spark portability with GPU performance.
Embrace a “data aware” approach to designing great UX
Data may seem like a trendy currency of the day, but we’ve always used data to inform design.
All the Data and Still Not Enough!
Claudia Perlich discusses tricks to the art of predictive modeling in situations where the right data is scarce.
Getting started with FPGAs
The O’Reilly Hardware Podcast: Field Programmable Gate Arrays are getting easier
Stop sweating the password and learn to love public key cryptography
Jerrod Chong explores the emerging FIDO U2F open standard and its elegant public key cryptography for two-factor authentication.
Configuration, credentials, and code in cloud-native apps
Kevin Hoffman adds to the concept of configuration, a classic app development factor.
Getting Started with Deep Learning using Keras and Python
Experiment with deep learning neural networks using Keras, a high-level alternative to TensorFlow and Theano. Get started by focusing on model structure, and avoid the complexity of numerical programming on GPUs. Play faster and go deep.
Design principles for digital services
Ten key design principles developed by the UK Government Digital Service to champion a culture that puts the user first and delivers the best, low-cost public services possible.
Fluent Python: The power of special methods
You’ve used Python for years. Do you really know it? Be brave and skin that Python. In this cut, Luciano Ramalho probes deep into special methods and the Data Model. Become fluent with idiomatic Python.