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General Applications of Neural Networks

This course teaches you to deploy the workhorse of modern machine learning frameworks: neural networks. We start with the simplest building block, the perceptron, and demonstrate how these are organized into feed forward neural networks. We then explore predictive capabilities in computer vision, natural language processing, and time series analysis. Different architectures are employed for specific application areas.

The breakdown for this course is as follows:

  • Data Topics
    • Neural networks: the perceptron, feed forward neural networks; computer vision: convolutional neural networks, importing and manipulating images, generating images; time series analysis: long short term memory networks, autocorrelation
  • Software Topics
    • Flask Applications
  • Sessions
    • S1: Multilayer Perceptron
    • S2: Feed Forward Neural Networks
    • S3: Computer Vision I
    • S4: Computer Vision II
    • S5: Applications with Flask
    • S6: Time Series Analysis
    • S7: Dashboards with Plotly Dash
  • Labs
    • L1: Neural Network Linearity
    • L2: Wine Quality Prediction
    • L3: Motor Impellar Quality Prediction
    • L4: Customer Forecasting
    • L5: Motor Impellar Flask Application
  • Project
    • P1: Monolithic Tic-Tac-Toe App
    • P2: Microservices Tic-Tac-Toe App
    • P3: Unit Tests for Flask Applications
    • P4: Continuous Integration for Flask Applications