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Machine Learning Workshop Using TensorFlow and Keras

This course gives you a strong foundation in deep learning using Keras and TensorFlow. The hands-on, workshop-style projects represent real-life scenarios, including collecting and cleaning up data,...

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Course Code WA2906
Duration 2 days
Available Formats Classroom

This course gives you a strong foundation in deep learning using Keras and TensorFlow. The hands-on, workshop-style projects represent real-life scenarios, including collecting and cleaning up data, designing a model, training the model with data, and making predictions.

Prerequisites

  • Basic programming experience in any language is needed. You will receive enough introduction to Python to complete this course.
  • Knowledge of calculus and linear algebra is recommended but not necessary.

Course Details

Outline

Workshop 1 - Tensorflow Basics

  • Learn about Python language, Numpy, Pandas and Tensorflow.

Workshop 2 - Gradient Descent

  • Learn how GD works and how machines learn using this technique.

Workshop 3 - Simple Linear Regression

  • Perform linear regression in a very simple problem domain. The goal is to learn how linear regression works.

Workshop 4 - Ames, Iowa House Price Prediction Using Neural Network

  • Learn the theory behind neural networks.
  • Apply neural network to solve a real life regression problem.

Workshop 5 - AirBnB Rent Prediction

  • This is a realistic regression problem. We try to predict property rental prices in the Boston area. We learn to work with categorical features like neighborhood and property type.
  • This workshop also shows the common techniques used to preprocess data.

Workshop 6 - Lung Capacity Prediction

  • This is a selfguided workshop. You will be given the dataset and the problem description.
  • You will need to solve the problem using a neural network.

Workshop 7 - Logistic Regression Using Gradient Descent

  • Learn the theory behind logistic regression (or classification).
  • Solve a simple classification problem using Gradient Descent.

Workshop 8 - Titanic Survivability Prediction

  • Solve a realistic classification problem using a neural network.

Workshop 9 - Fetal Monitoring Complication Prediction

  • Learn the theory behind multi-class classification.
  • Solve a medical classification problem using a neural network.

Workshop 10 - Credit Card Fraud Detection

  • In this workshop we get deeper into evaluating the quality of a model.
  • We learn about Confusion Matrix, Precision and Recall.

Workshop 11 - Epileptic Seizure Recognition

  • This is a selfguided workshop. You will be given the dataset and the problem description.
  • You will need to solve the problem using a neural network.

Workshop 12 - Basic Convolutional Neural Network (CNN)

  • The goal of this workshop is the understand the structure of a CNN. We learn about the convolution layer, max pooling layer, fully connected layer and readout layer. We solve the MNIST handwritten digit comprehension problem.

Workshop 13 - Theory of Convolutional Neural Network

  • Learn the theory behind matrix convolution. Observe how convolution works on images.

Workshop 14 - Handwritten Digit Recognition

  • Apply CNN to classify handwritten digit images.

Workshop 15 - Solve CIFAR-10 Challenge

  • This is a selfguided workshop.
  • CIFAR-10 dataset consists of 60000 32x32 colour images in 10 classes. We train a CNN that tries to classify images in those 10 classes.