Deep Learning

  Prerequisites To start, you need to play the version tracking game. First, make sure your graphics card can support CUDA by finding it on this list:  https://developer.nvidia.com/cuda-gpus . For example, laptop has a GeForce GTX 1060, which supports CUDA and Compute Capability 6.1. You can find the model of your graphics card by clicking in the Windows search bar and entering “dxdiag.” This tool will identify your system’s hardware. The  Display  tab should list your graphics card (if present on your computer). Then, we need to work backwards, as TensorFlow usually does not support the latest CUDA version (note that if you compile TensorFlow from source, you can likely enable support for the latest CUDA, but we won’t do that here). Take a look at  this chart to view the required versions of CUDA and cuDNN . At the time of writing, this is the most recent TensorFlow version and required software: Version Python version Compiler Build tools cuDNN CUDA tensorflow...

  What is Perceptron: A perceptron is a neural network unit (an artificial neuron) that does certain computations to detect features or  business intelligence  in the input data. And this perceptron tutorial will give you an in-depth knowledge of Perceptron and its activation functions. By the end of this tutorial, you’ll be able to: Explain artificial neurons with a comparison to biological neurons Implement logic gates with Perceptron Describe the meaning of Perceptron Discuss Sigmoid units and Sigmoid activation function in Neural Network Describe ReLU and Softmax Activation Functions Explain Hyperbolic Tangent Activation Function Let’s begin with understanding what is artificial neuron. Biological Neuron A human brain has billions of neurons. Neurons are interconnected nerve cells in the human brain that are involved in processing and transmitting chemical and electrical signals. Dendrites are branches that receive information from other neurons. Cell nucleus or Soma ...