Artificial intelligence #7 - maths of neural networks - forward pass

Welcome to edition #7

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I like the above diagram which shows the maths of neural networks (only the inference i.e. the forward pass - not the training). The diagram was created by Dr Rubens Zimbres. But I could not find a detailed explanation. In this edition, I try to explain the flow behind this diagram using basics of linear algebra. The discussion was created with Dr Amita Kapoor. I first heard of Amita through her co-author Antonio Gulli (Engineer Director, Office of CTO at Google London).We have used Antonio and Amita's book on deep learning for multiple Oxford courses now. Amita also works with me in Germany at Digitty as the lead data scientist.

Because of the diagrams and the length of the post, its not possible to post it directly here. Hence sharing as an attachment. hope you like it. Note that the backward pass (training) will be another blog - Maths of neural networks - forward pass

Some interesting jobs posted in my network

R and D data scientist in Korea - by Erel Rosenberg

Research associate for artificial intelligence for cancer research by Dr Christopher Yau

Multiple research research associates roles in Robotics

Scientific software development engineer at PARC by Dr Kalai Ramea

Principal Cloud Advocate at Microsoft Redmond via Jim Bennett and Francesca Lazzeri, PhD  We work closely with the Microsoft cloud team in Redmond at the #universityofoxford. So, happy to recommend this role.

Finally, an interesting book I am reading and recommend Daniel T Willingham’s the reading mind – a book about the science of reading and comprehension