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Flooding and fixed routing are methods to transmit data packets from the source to the destination through a number of intermediate routers connected by transmission lines.Flooding is a non-adaptive routing technique following this simple method − when a data packet arrives at a router, it is sent to all the outgoing links except the one it has arrived on.Fixed routing algorithm is a procedure that lays down a fixed route or path to transfer data packets from source to the destination. The route is a mathematically computed best path, i.e. “least–cost path” that the packet can be routed through. The ... Read More
Tensorflow can be used with estimators for feature engineering by first defining the columns and iterating through the categorical columns. The unique names of features are obtained, and is appended to an empty list.Read More: What is TensorFlow and how Keras work with TensorFlow to create Neural Networks?We will use the Keras Sequential API, which is helpful in building a sequential model that is used to work with a plain stack of layers, where every layer has exactly one input tensor and one output tensor.A neural network that contains at least one layer is known as a convolutional layer. We ... Read More
The titanic dataset can be visualized using the ‘hist’ method which visualizes a histogram. A horizontal bar graph can be generated by specifying the type of graph as ‘barh’. Read More: What is TensorFlow and how Keras work with TensorFlow to create Neural Networks?We will use the Keras Sequential API, which is helpful in building a sequential model that is used to work with a plain stack of layers, where every layer has exactly one input tensor and one output tensor.TensorFlow Text contains collection of text related classes and ops that can be used with TensorFlow 2.0. The TensorFlow Text can ... Read More
The titanic dataset can be explored using the estimator with Tensorflow by using the ‘head’ method, the ‘describe’ method, and the ‘shape’ method. The head method gives the first few rows of the dataset, and the describe method gives information about the dataset, such as column names, types, mean, variance, standard deviation and so on. The shape method gives the dimensions of the data.Read More: What is TensorFlow and how Keras work with TensorFlow to create Neural Networks?We will use the Keras Sequential API, which is helpful in building a sequential model that is used to work with a plain ... Read More
A linear model can be built with estimators to load the titanic dataset using the ‘read_csv’ method which is present in ‘Pandas’ package. This method takes google APIs that store the titanic dataset. The API is read and the data is stored in the form of a CSV file.Read More: What is TensorFlow and how Keras work with TensorFlow to create Neural Networks?We will use the Keras Sequential API, which is helpful in building a sequential model that is used to work with a plain stack of layers, where every layer has exactly one input tensor and one output tensor.A ... Read More
The ‘predict’ method is called on never before seen data and the predictions and the actual value is displayed on console.Read More: What is TensorFlow and how Keras work with TensorFlow to create Neural Networks?We will use the Keras Sequential API, which is helpful in building a sequential model that is used to work with a plain stack of layers, where every layer has exactly one input tensor and one output tensor.A neural network that contains at least one layer is known as a convolutional layer. We can use the Convolutional Neural Network to build learning model. TensorFlow Text contains collection ... Read More
Tensorflow can be used with the estimator to predict output on new data using the ‘predict’ method which is present in the ‘classifier’ method.Read More: What is TensorFlow and how Keras work with TensorFlow to create Neural Networks?We will use the Keras Sequential API, which is helpful in building a sequential model that is used to work with a plain stack of layers, where every layer has exactly one input tensor and one output tensor.A neural network that contains at least one layer is known as a convolutional layer. We can use the Convolutional Neural Network to build learning model. TensorFlow ... Read More
Suppose following is the problem:We have a sequence of numbers starting from 1 and upto any arbitrary number, let's call it num. We have to pick two such numbers from the sequence (let's call them m and n), such that:sum(1 to num) - (m + n) = m * nAnd finally, we should return an array of groups of all such numbers.For example −If the input is −const num = 10;Then the output should be −const output = [ [7, 6] ];because sum(1 to 10) = 55and, 55 - (6 + 7) = 6 * 7 = 42ExampleThe code ... Read More
Suppose, we have the following JSON object that may contain nesting upto any level −const obj = { "one": 1, "two": { "three": 3 }, "four": { "five": 5, "six": { "seven": 7 }, "eight": 8 }, "nine": 9 };We are required to write a JavaScript function that takes in one such nested JSON object and returns a new object that contains no nesting and maps the corresponding values to the keys using the dot ... Read More
Suppose, we have an array of numbers like this −const arr = [1, 6, 3, 1, 3, 1, 6, 3];We are required to write a JavaScript function that takes in one such array as the first and the only argument. Then the function should look for all such numbers in the array that appear for an odd number of times (excluding only once).For example, In the above array, the numbers 1 and 3 both appear for 3 times (odd), so our function should remove the third occurrence of both these numbers.And the output array should look like −const output = ... Read More