Artificial Neural Networks Training and Testing Process

In this video, we will cover the process of training and testing of AI models. Data set is generally divided into 80% for training and 20% for testing (numbers may vary). The Training dataset is used for training the model (i.e.: weights update). The Testing dataset is used for evaluating trained network performance. The brain has over 100 billion neurons communicating through electrical & chemical signals. Neurons communicate with each other and help us see, think, and generate ideas. Human brain learns by creating connections among these neurons. Artificial Neural Networks (ANNs) are information processing models inspired by the human brain. The neuron collects signals from input channels named dendrites, processes information in its nucleus, and generates an output in a long thin branch called axon. After model training, network weights are frozen and the network is tested with new data that the model has never seen before during training. #AI #ArtificialNeuralNetworks