Neural Networks and Deep Learning for Life Sciences and Health Applications

Description

This course offers an introduction to topics of neural networks and deep learning using Tensorflow. There is a focus on applications in life sciences. The course is recommended for professionals as well as beginners with a suitable background and interests.

At a glance

Qualification: Certificate of attendance

Duration: 30-36 contact lessons

Costs: CHF 760.00

Comment on costs: 760 regular

360 student

Location: Lagerstrasse 41

8021 Zürich

Language of instruction: English
English

Objectives and content

Target audience

This course is for professionals as well as students.

It is addressed to people who are willing to learn what deep learning is. You should be someone who has some background in programming (not necessarily in Python) and some background in mathematics. If you are a beginner, we will cover the basics you need, but you may need to work a bit more on your own during the classroom lectures.

Objectives

TOPICS

Review of Python and numpy, Matplotlib, review of linear algebra, computational graphs, introduction to tensorflow,  network with one neuron, logistic and linear regression with one neuron, neural networks with many layers, overfitting, weights initialization, gradient descent algorithm, dynamical learning rate decay, optimizers (Momentum, RMSProp, Adam), regularization: L1, L2 and dropout, metric analysis, hyperparameter tuning, grid search, random search, bayesian optimization, coarse to fine optimization, parameter search on a logarithmic scale

Enquiries and contact

Provider

Instructors

Umberto Michelucci (main lecturer)

Offered in cooperation with

Umberto Michelucci (Helsana)

4quant

Application

Admission

see: https://deeplearning.lifeinnumbers.ws-hp-ias.ch/

Information for applicants

see: https://deeplearning.lifeinnumbers.ws-hp-ias.ch/

Starting October 2018

General terms and conditions

Conditions

Downloads and brochure