Keras - Python Deep Learning Neural Network API

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Deploy Keras Neural Network to Flask web service | Part 1 - Overview

May 10, 2018 by


Over the next several videos, we’ll be working to deploy a Keras model to a Flask web service. In this first video, we’re going to discuss what this means and why we’d want to do this. We’ll also get a glimpse of what the final product will look like. The model we’ll use is the fine-tuned VGG16 image classifier that we worked with earlier in this playlist to predict on images of cats and dogs, but the steps we go through together for this can be used for whatever model you choose to work with. Once we’ve deployed our Keras model to the web service, we’ll be able to access our model over HTTP from other apps, and we’ll even see how we can interact with our model from the browser. Our end goal will be to deploy the trained model to a Flask web service, and then from the browser, send an image of a cat or dog to the web service, and have it respond with the model’s predictions. 💥🦎 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.