A tuple is an assortment of items which requested and permanent. Tuples are successions, very much like records. The contrasts among tuples and records are, the tuples can't be changed not normal for records and tuples use enclosures, though records utilize square sections. Making a tuple is pretty much as straightforward as putting diverse comma-isolated qualities. Alternatively you can put these comma-isolated qualities between enclosures moreover. For instance − tup1 = ('material science', 'science', 1997, 2000); tup2 = (1, 2, 3, 4, 5 ); tup3 = "a", "b", "c", "d"; The void tuple is composed as two enclosures containing nothing − tup1 = (); To compose a tuple containing a solitary worth you need to incorporate a comma, despite the fact that there is just one worth − tup1 = (50,); Like string files, tuple records start at 0, and they can be cut, linked, etc. Getting to Values in Tuples To get to values in tuple, u...
Figure. Activation Function Activation functions are a very important component of neural networks in deep learning. It helps us to determine the output of a deep learning model, its accuracy, and also the computational efficiency of training a model. They also have a major effect on how the neural networks will converge and what will be the convergence speed. In some cases, the activation functions might also prevent neural networks from convergence. So, let’s understand the activation functions , types of activation functions & their importance and limitations in detail. What is the activation function? Activation functions help us to determine the output of a neural network. These types of functions are attached to each neuron in the neural network, and determines whether it should be activated or not, based on whether each neuron’s input is relevant for the model’s prediction. Activation function also helps us to normalize the output of each neuron ...