Description:

This masterclass is an introduction to deep learning applications in the social sciences. It offers a step-by-step guide to working with basic classification tasks, image recognition using convolutional neural networks (CNNs), and natural language processing (NLP) with recurrent neural networks (RNNs). The course utilizes Python, TensorFlow, and Google Colab but does not require prior coding experience. These foundational tools provide practical experience in applying essential deep learning techniques to the social sciences domain.

This masterclass is part of the ACSPRI suite of courses in social data science and does not require prior knowledge of machine learning or Python programming.

Start: Wednesday, 09 October 2024 @ 09:30

End: Friday, 11 October 2024 @ 16:00

Duration: 3 days

Timezone: Melbourne

Venue: Online

 Country: Australia

Prerequisites:

The course requires understanding of a basic of statistical concepts, exposure to machine learning foundations is beneficial as well, such as ACSPRI's Machine Learning for Data Science: Surpervised Learning Techniques

The course assumes no prior knowledge of Python, though some programming experience (e.g. using R) is beneficial.

Learning Objectives:

This course is tailored for social scientists, PhD students, and researchers who aim to use machine learning techniques in their work. It will particularly benefit those interested in using large datasets for uncovering patterns within complex social behaviours. Additionally, marketing specialists and business strategists will find the course's practical focus on real-world applications invaluable to gain consumer insights from social media and other digital platforms. No prior expertise in programming is necessary, making it accessible to a wide audience keen on bringing data-driven decision-making into their respective fields.

Eligibility:
  • Open to all

Organiser: ACSPRI

Contact: info@acspri.org.au

Host institution: ACSPRI

Keywords: Deep learning, Python, CNN, NLP, RNN, Neural networks

Fields: ENVIRONMENTAL SCIENCES, BIOLOGICAL SCIENCES, MEDICAL AND HEALTH SCIENCES, EDUCATION, ECONOMICS, STUDIES IN HUMAN SOCIETY, PSYCHOLOGY AND COGNITIVE SCIENCES, LAW AND LEGAL STUDIES, LANGUAGE, COMMUNICATION AND CULTURE

Target audience:
  • researchers
  • HDR students
  • PhD students
  • Social Scientists

Capacity: 12

Event type:
  • Workshop
Tech Requirements:

This workshop will take place online.

BYO Laptop + Zoom. Both PC and MAC are great

The course uses Google Colab and requires a Google account (please make sure you have one or please register one before the session)

All course materials will be provided

Cost Basis: Cost incurred by all

Introduction to Deep Learning for Social Sciences https://dresa.org.au/events/introduction-to-deep-learning-for-social-sciences This masterclass is an introduction to deep learning applications in the social sciences. It offers a step-by-step guide to working with basic classification tasks, image recognition using convolutional neural networks (CNNs), and natural language processing (NLP) with recurrent neural networks (RNNs). The course utilizes Python, TensorFlow, and Google Colab but does not require prior coding experience. These foundational tools provide practical experience in applying essential deep learning techniques to the social sciences domain. This masterclass is part of the ACSPRI suite of courses in social data science and does not require prior knowledge of machine learning or Python programming. 2024-10-09 09:30:00 UTC 2024-10-11 16:00:00 UTC ACSPRI Online, Australia Online Australia ACSPRI info@acspri.org.au [] researchersHDR studentsPhD studentsSocial Scientists 12 workshop open_to_all Deep learning PythonCNNNLPRNNNeural networks