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Part 2: Deep Learning FPGA Acceleration with Python - 'Inference'

Overview In this we develop out our hardware acceleration library to handle inference for a MLP neural network using the Fisher Iris dataset.

Part 1: Deep Learning FPGA Acceleration with Python - 'Quantization and Data Pipelines'

Overview This is a project aimed at building custom per-model hardware accelerators for machine learning systems to reduce overall time and power cost in inference and training.

How to finetune a model then deploy it to the web: Part 2 - 'Inference with Python and JavaScript'

Overview This is part two of a two-part blog series. If you haven’t read part 1, I reccomend you do so first to get caught up to this point.

How to finetune a model then deploy it to the web: Part 1 - 'Training by finetuning'

Overview One problem with getting started with ML nowadays is how daunting some of the ‘interesting’ things can be.

What the Heck is Serverless

Whatever your technical expertise this will be a nice introduction to serverless and the pros/cons.

Machine Learning (Usually) isn't the Right Solution

This is a weird one. As someone who has made their living from machine learning this probably isn’t what you’d expect.