Abstract: Agenda • Why do we need to create our own models? • Introduction to Deep Learning • Lab: The “Hello World” of TensorFlow + Keras: Logistic Regression
• Convolutional Neural Networks: At last! Real Deep Learning • Lab: Computer Vision with CNNs • Beyond Computer Vision
Developers interested in building deep learning models, and researchers interested in comparing the specific implementation with other frameworks. No previous experience is required, as all concepts will be introduced in the theory modules of the workshop; however, a minimum knowledge of Machine Learning concepts and practices (such as understanding the train / test / validation cycle, etc...) would be beneficial.
The following labs will be done during the course of the workshop:
• Environment set up • Basic Logistic Regression • MNIST classifier (guided) o Logistic Regression o CNN • Playing with the hyperparameters: o Minibatch sizes o Learning Rates • MNIST classifier challenge (your turn!)
We will perform the installation of the required wheels for using TensorFlow as part of the labs, but having the following pre-requisites installed will save time and potential issues
during the workshop: • Anaconda distribution with Python 3.5 environment • Python IDE (VSCode recommended)• Git client
Bio: Pablo Doval is Principal Data Architect and the General Manager of Plain Concepts in the UK. With a background of relational databases, data warehousing and traditional BI projects, he has spent the last years architecting and building Big Data and Machine Learning projects for customers in different sectors, such as Healthcare, Digital Media, Retail and Industry.
Principal Data Architect at Plain Concepts