Neural Network Mathematics: Understanding the Mathematics of a Neuron
Math | Intermediate
- 7 videos | 50m 16s
- Includes Assessment
- Earns a Badge
First conceived in the 1940s, it wasn't until the early 2010s that artificial neurons showed their true potential as layered entities in the form of neural networks. When big data processing using distributed computing became mainstream, the computational capacity was now available to train these neural networks on huge datasets. Knowing this is one thing, but understanding how it all works is where the true potential lies. Use this course to gain an intuitive understanding of how neural networks work. Explore the mathematical operations performed by a single neuron. Recognize the potential of thousands of neurons connected together in a well-architected design. Finally, implement code to mathematically perform the operations in a single layer of neurons working on batch input. When you're finished, you'll have a solid grasp of the mechanisms behind neural networks and the math behind neurons.
WHAT YOU WILL LEARN
discover the key concepts covered in this courserecall the architecture and components that make up neural networkssummarize the mathematical operation of a neuroninstall Python modules
compute the weighted sum of inputs with biasprocess data in batches and with multiple layerssummarize the key concepts covered in this course
IN THIS COURSE
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