handwritten digits with tensorflow written by ellie birbeck edited by brian hogan neural networks are used as method of deep learningone of the many subfields of artificial intelligence they were first proposed around years ago as an attempt at simulating the way the human brain worksthough in much more simplified form individual 'neuronsare connected in layerswith weights assigned to determine how the neuron responds when signals are propagated through the network previouslyneural networks were limited in the number of neurons they were able to simulateand therefore the complexity of learning they could achieve but in recent yearsdue to advancements in hardware developmentwe have been able to build very deep networksand train them on enormous datasets to achieve breakthroughs in machine intelligence these breakthroughs have allowed machines to match and exceed the capabilities of humans at performing certain tasks one such task is object recognition though machines have historically been unable to match human visionrecent advances in deep learning have made it possible to build neural networks which can recognize objectsfacestextand even emotions in this tutorialyou will implement small subsection of object recognition--digit recognition (an using open-source tensorflow python library developed by the google brain labs for deep learning researchyou will