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Neural Network Visualizer Web App with Python
  • Level Intermediate
  • Duration 3 hours
  • Offered by

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In this 2 hour long project-based course, you will learn to create a Neural Network Visualizer web application using Streamlit, and a simple model server using Keras and Flask. You will also use Keras to train a Neural Network model, and use Keras' functional API to create a model with multiple outputs. We will create a web application that will visualize the outputs of all the nodes of all the layers of the neural network for a given input image. In order to complete this project successfully, you will need prior programming experience with Python, understanding of the theory behind neural networks, and familiarity with Keras. Note: This course works best for learners who are based in the North America region. We're currently working on providing the same experience in other regions.

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Dive into the exciting world of data science and AI with the "Neural Network Visualizer Web App with Python" course. This project-based learning experience, crafted by Coursera, is designed to equip you with the skills to create a powerful Neural Network Visualizer web application using Streamlit, alongside a simple model server via Keras and Flask. Over the span of 2 hours, you will gain hands-on experience in training a Neural Network model using Keras, and leveraging the Keras functional API to develop a model with multiple outputs. The highlight of this course is the creation of a web application that vividly visualizes the outputs of all nodes across the neural network layers for any given input image. Ideal for professionals with a solid background in Python programming, neural network theory, and Keras, this course promises a rich, interactive learning journey. Although currently optimized for learners in North America, we’re working on expanding this experience globally. Enroll through the Coursera Starter subscription to elevate your AI and data science prowess. This course is meticulously designed for professionals eager to deepen their expertise and create cutting-edge AI applications.