Introduction to Tensorflow
This is a workshop to get students familiar with the basics of Tensorflow. We will explore concepts and go through examples and student exercises on Google Colab. Students will review neural networks and the components of a basic neural network. Then, they’ll use the TensorFlow Playground to explore the components of a neural network and how each component interacts with others. Finally, they’ll set up Google Colaboratory to execute “cloud-based Jupyter Notebooks” and build their own neural network model. By the end of this workshop, students will be able to: * Compare the traditional machine learning classification and regression models with the neural network models * Describe the perceptron model and its components * Understand the concepts of a basic neural network * Run cloud-based Jupyter Notebooks with Google Colaboratory * Implement neural network models using TensorFlow
Introduction to Neural Networks and Tensorflow Build Your First Neural Network Prepare Your Neural Network Datasets Dig Deeper Into Neural Networks Select the Best Model for Your Dataset Export and Import Trained Models Application
Students should have some basic familiarity with Python and Machine Learning.
- Learn how to apply Tensorflow to build Neural Networks.