Skip to content

Latest commit

 

History

History
49 lines (23 loc) · 2.04 KB

File metadata and controls

49 lines (23 loc) · 2.04 KB

intro2DL

The key advancement in the field of artificial intelligence is Neural Networks, yet most people don’t understand how they really work!

Join us on 13th of June to demystify the black box of Neural Networks and break them into bits and pieces. We’ll start by defining Deep Learning and then explain its basic unit, Neural Networks: what are they, what’s the intuition behind them, why now, how they learn, etc.

This is a technical workshop, so expect to get your hands dirty with Python. You will build your first Neural Network using the most common deep learning framework, TensorFlow.

MAKE SURE to register: https://ihjoz.com/events/4654-intro-to-deep-learning-with-tensorflow

image

We will solve two Examples:

1st Example: Regression (Boston House Prices Prediction)

This example builds a model to predict the median price of homes in a Boston suburb during the mid-1970s. To do this, we'll provide the model with some data points about the suburb, such as the crime rate and the local property tax rate.

image

2nd Example: Classification (Fashion MNIST)

We train a neural network model to classify images of clothing, like sneakers and shirts.

image

👇 👇 👇 👇 👇 👇 👇 👇 👇 👇

Slides can be found here: https://drive.google.com/file/d/1Dk0vLxE4r-pMGe-ys4bTIfYsmk9EmprP/view?usp=sharing

Code (with blanks) on Google Colab can be found here: https://colab.research.google.com/drive/1ZoK_UI4unnBJwBj_pimq4TlTG37ntz_X

Complete code (with solutions) can be found here: https://colab.research.google.com/drive/1zoynwe4ZPDIpuE1uWV7-Z-Wz6GLgo-U6

To edit the code, click File then Save a copy in Drive…


Happy coding 💻

Live Love AI 😍

Instructor

This workshop was prepared and presented by Obeida ElJundi