• AI for Time Series Prediction

    Princeton Public Library

    We will learn how a deep learning framework can be used for sound classification, stock prediction, and other events that have a time dependency. Please attend all classes within the series and consider bringing a laptop. The series continues Mondays, June 10, 17, 24. At the first class we will decide on the project we are going to create throughout the class. Bring your ideas!

    2
  • Fundamental of AI

    Princeton Public Library

    AI Algorithms: Neural Networks Session 1 In this two month series, we will go through each step of the implementation of a deep learning algorithm. We will see each detail of a forward neural net, the CNN and the LSTM. Requirements: Basic Linear Algebra, Basic Python (or good programming level in another language), and Calculus. In this first session, we will create a simple feed forward network with one hidden layer and one kind of activation function. Please attend all classes within the series and consider bringing a laptop. The series continues Wednesdays, May 8, 15, 22, 29; and June 5, 12, 19, 26.

    1
  • AI for Time Series Prediction

    Princeton Public Library

    We will learn how a deep learning framework can be used for sound classification, stock prediction, and other events that have a time dependency. Please attend all classes within the series and consider bringing a laptop. The series continues Mondays, June 10, 17, 24. At the first class we will decide on the project we are going to create throughout the class. Bring your ideas!

    7
  • Fundamental of AI

    Princeton Public Library

    AI Algorithms: Neural Networks Session 1 In this two month series, we will go through each step of the implementation of a deep learning algorithm. We will see each detail of a forward neural net, the CNN and the LSTM. Requirements: Basic Linear Algebra, Basic Python (or good programming level in another language), and Calculus. In this first session, we will create a simple feed forward network with one hidden layer and one kind of activation function. Please attend all classes within the series and consider bringing a laptop. The series continues Wednesdays, May 8, 15, 22, 29; and June 5, 12, 19, 26.

  • AI for Time Series Prediction

    Princeton Public Library

    We will learn how a deep learning framework can be used for sound classification, stock prediction, and other events that have a time dependency. Please attend all classes within the series and consider bringing a laptop. The series continues Mondays, June 10, 17, 24. At the first class we will decide on the project we are going to create throughout the class. Bring your ideas!

    10
  • Reunions Project!

    Princeton Public Library

    Time for us to get together and go through the advances. For those who don't know about this project, We are building a project that might lead to a startup based on the computer vision classes. It targets those who included their name at the spreadsheet: https://docs.google.com/spreadsheets/d/1ywVq3JlhRwgtDg60MdMhN84jnmqiCOVh5m10ObeEdTk/edit#gid=[masked] Every business series will finish with some project like this.

  • Fundamental of AI

    Princeton Public Library

    AI Algorithms: Neural Networks Session 1 In this two month series, we will go through each step of the implementation of a deep learning algorithm. We will see each detail of a forward neural net, the CNN and the LSTM. Requirements: Basic Linear Algebra, Basic Python (or good programming level in another language), and Calculus. In this first session, we will create a simple feed forward network with one hidden layer and one kind of activation function. Please attend all classes within the series and consider bringing a laptop. The series continues Wednesdays, May 8, 15, 22, 29; and June 5, 12, 19, 26.

    2
  • Reunions Project!

    Princeton Public Library

    Time for us to get together and go through the advances. For those who don't know about this project, We are building a project that might lead to a startup based on the computer vision classes. It targets those who included their name at the spreadsheet: https://docs.google.com/spreadsheets/d/1ywVq3JlhRwgtDg60MdMhN84jnmqiCOVh5m10ObeEdTk/edit#gid=[masked] Every business series will finish with some project like this.

  • Fundamental of AI

    Princeton Public Library

    AI Algorithms: Neural Networks Session 1 In this two month series, we will go through each step of the implementation of a deep learning algorithm. We will see each detail of a forward neural net, the CNN and the LSTM. Requirements: Basic Linear Algebra, Basic Python (or good programming level in another language), and Calculus. In this first session, we will create a simple feed forward network with one hidden layer and one kind of activation function. Please attend all classes within the series and consider bringing a laptop. The series continues Wednesdays, May 8, 15, 22, 29; and June 5, 12, 19, 26.

  • Reunions Project!

    Princeton Public Library

    Time for us to get together and go through the advances. For those who don't know about this project, We are building a project that might lead to a startup based on the computer vision classes. It targets those who included their name at the spreadsheet: https://docs.google.com/spreadsheets/d/1ywVq3JlhRwgtDg60MdMhN84jnmqiCOVh5m10ObeEdTk/edit#gid=[masked] Every business series will finish with some project like this.