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Introduction to Deep Neural Networks with Keras/TensorFlow

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Deep Neural Networks (DNNs) are used as a machine learning method for both regression and classification problems. Keras is a high-level, Python interface running on top of multiple neural network libraries, including the popular library TensorFlow. In this workshop, participants will learn how to quickly use the Keras interface to perform nonlinear regression and classification with standard fully-connected DNNs, as well as image classification using Convolutional Neural Networks (CNNs). We will also look at regularization techniques and how to deal with under- and over-fitting. All examples will use Python; some familiarity with Python is recommended. Computers will be available to complete exercises. We will run the models using Google Colab, which requires a Google account.

Introduction to Deep Neural Networks with Keras/TensorFlow

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Deep Neural Networks (DNNs) are used as a machine learning method for both regression and classification problems. Keras is a high-level, Python interface running on top of multiple neural network libraries, including the popular library TensorFlow. In this workshop, participants will learn how to quickly use the Keras interface to perform nonlinear regression and classification with standard fully-connected DNNs, as well as image classification using Convolutional Neural Networks (CNNs). We will also look at regularization techniques and how to deal with under- and over-fitting. All examples will use Python; some familiarity with Python is recommended. Computers will be available to complete exercises. We will run the models using Google Colab, which requires a Google account.

Introduction to Deep Neural Networks with Keras/Tensorflow

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Deep Neural Networks (DNNs) are used as a machine learning method for both regression and classification problems. Keras is a high-level, Python interface running on top of multiple neural network libraries, including the popular library TensorFlow. In this workshop, participants will learn how to quickly use the Keras interface to perform nonlinear regression and classification with standard fully-connected DNNs, as well as image classification using Convolutional Neural Networks (CNNs). We will also look at regularization techniques and how to deal with under- and over-fitting. All examples will use Python; some familiarity with Python is recommended.

 Deep Neural Networks with TensorFlow: A Quick Start Introduction

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Deep Neural Networks (DNNs) are used as a machine learning method for both regression and classification problems. TensorFlow is a popular software library that is often used to construct and train DNNs. In this workshop, participants will learn how to quickly use the high-level TensorFlow Estimator module to perform nonlinear regression and classification with standard fully connected DNNs. We will also show how the Estimator module can be used to perform image classification using Convolutional Neural Networks (CNNs). All examples will use Python; some familiarity with Python is recommended. You are encouraged but not required to bring a laptop with TensorFlow already installed.