PyData Amsterdam

https://pydata.org/amsterdam2018/schedule/presentation/30/

Hands-on introduction to Deep Learning with Keras and Tensorflow

Audience level: Novice Description Deep Learning has already conquered areas such as image recognition, NLP, voice recognition, and is a must-know tool for every Data Practitioner. This tutorial for aspiring Deep Learners will consist of a quick blunt Deep Learning overview followed by a hands-on tutorial that will teach you how to get started using Keras and Tesorflow.

Abstract Deep Learning has already conquered areas such as image recognition, NLP, voice recognition, and is a must-know tool for every Data Practitioner. This tutorial for aspiring Deep Learners will consist of a quick blunt Deep Learning overview followed by a hands-on tutorial that will teach you how to get started using Keras and Tesorflow.

This tutorial is for people that know the fundamentals of machine learning have a worked with the PyData stack have no deep learning hands-on experience with Keras Curriculum Deep Learning landscape Deep Learning tools in Python Blunt review of the Keras API (Hands-on) Build a deep learning model for an easy image classification dataset (Hands-on) Play around and optimize deep learning model for a harder dataset (Hands-on) Prerequisites Experience with Python and jupyter notebooks Keras or Tensroflow (version >= 1.4) installed Note: Some of the material is a repeat of the Code Breakfast Deep Learning session of January 17, 2018