Keras - Python Deep Learning Neural Network API

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Deploy Keras neural network to Flask web service | Part 8 - Access model from Powershell, Curl

May 25, 2018 by


Let's see how we can get predictions from our Keras model in a slightly different way than how we’ve seen it done in the browser. Here, we’ll be calling our back end Flask web service from both Powershell on Windows, and cURL in a Bash terminal. You may recall that, in the first video in this series on deploying a Keras model to Flask, I stated that once our model is being hosted by Flask, we’ll be able to interact with that model over HTTP regardless of which programming language our front end application is written in. We’ve seen all the details for how to build a front end web applciation with Javascript and HTML that runs in the browser and requests predictions from our model. Now, we’re going to get an idea for how easy it is to access our model using other languages and platforms. We’re first going to show how this is done using Powershell on a Windows machine. And we’ll then see how this is done using cURL in a Bash terminal. 💥🦎 DEEPLIZARD COMMUNITY RESOURCES 🦎💥 👀 OUR VLOG: 🔗 👉 Check out the blog post and other resources for this video: 🔗 💻 DOWNLOAD ACCESS TO CODE FILES 🤖 Available for members of the deeplizard hivemind: 🔗 🧠 Support collective intelligence, join the deeplizard hivemind: 🔗 🤜 Support collective intelligence, create a quiz question for this video: 🔗 🚀 Boost collective intelligence by sharing this video on social media! ❤️🦎 Special thanks to the following polymaths of the deeplizard hivemind: yasser Prash 👀 Follow deeplizard: Our vlog: Twitter: Facebook: Patreon: YouTube: Instagram: 🎓 Other deeplizard courses: Reinforcement Learning - NN Programming - DL Fundamentals - Keras - TensorFlow.js - Data Science - Trading - 🛒 Check out products deeplizard recommends on Amazon: 🔗 📕 Get a FREE 30-day Audible trial and 2 FREE audio books using deeplizard’s link: 🔗 🎵 deeplizard uses music by Kevin MacLeod 🔗 🔗 ❤️ Please use the knowledge gained from deeplizard content for good, not evil.