£600 – £1,080

Data Science Masterclass: Neural Networks & Deep Learning

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ASI Office

54 Welbeck Street

London

W1G 9XS

United Kingdom

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Refunds up to 7 days before event

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Description

Why sign up for this course?

On this course you get expert tuition from world-leading data scientists. Our in-person courses allow you to meet and connect with other data science practioners and broaden your network. You will further receive free access to our proprietary data science platform SherlockML and for up to 90 days after the course.

Course Description

This course will take you through everything you need to know to understand neural networks. This course is designed for novices in neural nets, and will take you step by step along the way of building neural nets. We’ll demonstrate how to go from fitting linear regressions, to fitting highly non-linear functions to generic datasets. During this course, you will build your own learning algorithm rather than using pre-packaged libraries. This allows you to develop a deep understanding of optimization of neural nets, rather than learning how to operate a black box. The workshop consists of a mixture of lectures and practical exercises in Jupyter notebooks. You will get plenty of chance to ask and learn from our experts in the field of deep learning.

Neural nets are used for:

  • Regression analysis and (non-linear) time series prediction

  • Classification problems, including pattern and sequence recognition, novelty detection and sequential decision making

  • Data processing, including filtering and clustering.

And are currently applied in across a wide range of areas such as object recognition, speech recognition, natural language processing, medical diagnosis, automated trading systems, vehicle control, game playing etc.

Learning Objectives

At the end of this course, participants should be able to

  • Set-up a basic neural network from scratch
  • Understand how to train a neural network and optimize its parameters
  • Implement neural networks on a broad set of problems


Who Should Attend

This class is intended for data science practitioners and data engineers who want to explore deep learning.

Teachers

At the ASI you receive expert tuition from experienced practitioners. Our courses are developed by a team of experienced Machine Learning practitioners, who hold Doctorate Degrees in Science or Computer Science. The ASI has a wealth of experience across different industries, having delivered over 150 commercial data science projects and provided corporate training for three years. This course is taught by Dr Ilya Feige, Head of Research at ASI Data science

Dr Feige is the Head of Research at ASI Data Science and an Honorary Senior Research Associate at University College London. He studies machine learning at the intersections of industry and academia. His formal background is in theoretical particle physics, in which he received his PhD from Harvard University. He has also worked in management consulting at Mckinsey & Company, and uses this lens to keep a clear view of value to the private sector in his research.

Prerequisites

  • Experience working with Python

  • Familiar with machine learning regressions

  • Familiar with the Numpy library

Also:

  • Please try signing up to SherlockML by using the invite code distributed before the start of the course (https://sherlockml.com/)

  • Please bring your laptop for this course

Course outline

  1. Comparing linear, logistic regression frameworks to neural nets
  2. Neural networks as a framework for fitting data with general nonlinear functions
  3. Working with higher dimensional data
  4. Learning and training neural networks
  5. Advanced topics
  6. Q&A with experts


Questions?

Please reach out to training@asidatascience.com should you have any questions regarding this course.

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Date and Time

Location

ASI Office

54 Welbeck Street

London

W1G 9XS

United Kingdom

View Map

Refund Policy

Refunds up to 7 days before event

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