Image Classification with the Elastic Stack and TensorFlow
In recent years, Convolutional Neural Networks (CNNs) have shown remarkable performance in many computer vision tasks, such as object recognition. In this course, you’ll explore the most popular deep learning library — Google's TensorFlow — and how it can be used with the Elastic Stack to build a contextual image classification system. Essential concepts are presented, such as TensorFlow data types, data structures, and how to create a convolutional neural networks to perform deep learning on visual data. In a series of labs, these concepts are put into practice and the results are shared to the Elastic Stack for searching, analyzing, and visualizing. After completing this course you will be able to build a deep learning neural network with TensorFlow and share that information back into the Elastic Stack.
- TensorFlow Basics and Architecture
- TensorFlow Libraries and Extensions
- Neural Networks
- Queries and Aggregations of Visual Data
This course is a module of the Data Science specialization. Find out how our focused Training Specializations can help you with your use case.
Data Scientists, Software Developers
Virtual Classroom - 1 Day | 2-3 hours
- We recommend you have taken Elasticsearch Engineer I and Elasticsearch Engineer II or possess equivalent knowledge. Engineer I and Engineer II teach the concepts that are the foundation upon which all specializations are built.
- Some exposure to machine learning concepts
- Basic Python
- Stable internet connection
- Mac, Linux, or Windows
- Latest version of Chrome or Firefox (Safari is not 100% supported)
Upcoming Classes — Image Classification with the Elastic Stack and TensorFlow
It was awesome. Both instructors are great speakers. They have a wide and deep knowledge about the topic, and they know how to pass it on. They are infecting with their enthusiasm.