Scalar or constant values are defined once, and they are repeated across all rows/entries of the series data structure. Following is an example −Example Live Demoimport pandas as pd my_index = ['ab', 'mn' ,'gh', 'kl'] my_series = pd.Series(7, index = my_index) print("This is series data structure created using scalar values and ... Read More

Visualizing data is an important step since it helps understand what is going on in the data without actually looking at the numbers and performing complicated computations. Seaborn is a library that helps in visualizing data.Scatter plot shows the distribution of data as data points that are spread/scattered on the ... Read More

Let us see how a series data structure can be created with the help of a Numpy array, and explicitly giving values for ‘index’.When no value is specified for index, default values beginning from 0 are assigned to values in the series.Following is an example −Example Live Demoimport pandas as pd ... Read More

A neuron is a mathematical function that takes one or more values as input and outputs a ingle numerical value −It can be defined as follows −Here, ‘f’ refers to the function.We first computed the weighted sum of the inputs xi and the weights wiThe weight wi is also known ... Read More

A neural network can be understood as a network of hidden layers, an input layer and an output layer that tries to mimic the working of a human brain.The hidden layers can be visualized as an abstract representation of the input data itself. These layers help the neural network understand ... Read More

The basic example of a neural network is a ‘perceptron’. It was invented by Frank Rosenblatt in 1957. The perceptron is a classification algorithm similar to logistic regression. This because, similar to logistic regression, a perceptron has weights, w, and an output function, ‘f’, which is a dot product of ... Read More

Neural networks have been around for many years, through which they have been praised as well as criticised for their characteristics.But off late, they have gained attention over other machine learning algorithms. Of course, Machine learning algorithms are important as they help achieve certain goals. But what should we do ... Read More

We previously understood how Q-learning works, with the help of Q-value and Q-table. Q-learning is a type of reinforcement learning algorithm that contains an ‘agent’ that takes actions required to reach the optimal solution. This is achieved with the help of Q-table that is present as a neural network. It ... Read More

Q-learning is a type of reinforcement learning algorithm that contains an ‘agent’ that takes actions required to reach the optimal solution.Reinforcement learning is a part of the ‘semi-supervised’ machine learning algorithms. When an input dataset is provided to a reinforcement learning algorithm, it learns from such a dataset, otherwise it ... Read More

We will be writing two JavaScript functions, the job of both the functions will be to take in a number and return its factorial.The first function should make use of a for loop or while loop to compute the factorial. Whereas the second function should compute the factorial using a ... Read More