Answer: Backpropagation is the essence of neural network training. It is the method of fine-tuning the weights of a neural network based on the error rate obtained in the previous epoch (i.e., iteration). Proper tuning of the weights allows you to reduce error rates and make the model reliablRead more
Answer:
Backpropagation is the essence of neural network training. It is the method of fine-tuning the weights of a neural network based on the error rate obtained in the previous epoch (i.e., iteration). Proper tuning of the weights allows you to reduce error rates and make the model reliable by increasing its generalization.
Backpropagation in neural network is a short form for “backward propagation of errors.” It is a standard method of training artificial neural networks. This method helps calculate the gradient of a loss function with respect to all the weights in the network.
Back propagation algorithm:
The Back propagation algorithm in neural network computes the gradient of the loss function for a single weight by the chain rule. It efficiently computes one layer at a time, unlike a native direct computation. It computes the gradient, but it does not define how the gradient is used. It generalizes the computation in the delta rule.
Advantages of Backpropagation :
Most prominent advantages of Backpropagation are:
Backpropagation is fast, simple and easy to program
It has no parameters to tune apart from the numbers of input
It is a flexible method as it does not require prior knowledge about the network
It is a standard method that generally works well
It does not need any special mention of the features of the function to be learned.
Types of Backpropagation :
Two Types of Backpropagation Networks are:
Static Back-propagation
Recurrent Backpropagation
Static back-propagation:
It is one kind of backpropagation network which produces a mapping of a static input for static output. It is useful to solve static classification issues like optical character recognition.
Recurrent Backpropagation:
Recurrent Back propagation in data mining is fed forward until a fixed value is achieved. After that, the error is computed and propagated backward.
The main difference between both of these methods is: that the mapping is rapid in static back-propagation while it is nonstatic in recurrent backpropagation.
Question 1 List and explain different types of testing done during the testing phase. Answer: Follow below link for answer: https://sikshapath.in/question/forward-engineering-is-not-necessary-if-an-existing-software-product/ Question 2 Analyze the role of testing tools in maintaining tRead more
Question 1
List and explain different types of testing done during the testing phase.
The purpose of reverse-engineering is to find out how an object or system works. There are a variety of reasons to do this. Reverse-engineering can be used to learn how something works and to recreate the object or to create a similar object with added enhancements. Often the goal of reverse-engineeRead more
The purpose of reverse-engineering is to find out how an object or system works. There are a variety of reasons to do this. Reverse-engineering can be used to learn how something works and to recreate the object or to create a similar object with added enhancements.
Often the goal of reverse-engineering software or hardware is to find a way to create a similar product more inexpensively or because the original product is no longer available. Reverse-engineering in information technology is also used to address compatibility issues and make the hardware or software work with other hardware, software or operating systems that it wasn’t originally compatible with.
How does the reverse-engineering process work?
The reverse-engineering process is specific to the object on which its being performed. However, no matter the context, there are three general steps common to all reverse-engineering efforts. They include:
Information extraction. The object being reverse-engineered is studied, information about its design is extracted and that information is examined to determine how the pieces fit together. In software reverse-engineering, this might require gathering source code and related design documents for study. It may also involve the use of tools, such as a disassembler to break apart the program into its constituent parts.
Modeling. The collected information is abstracted into a conceptual model, with each piece of the model explaining its function in the overall structure. The purpose of this step is to take information specific to the original and abstract it into a general model that can be used to guide the design of new objects or systems. In software reverse-engineering this might take the form of a data flow diagram or a structure chart.
Review. This involves reviewing the model and testing it in various scenarios to ensure it is a realistic abstraction of the original object or system. In software engineering this might take the form of software testing. Once it is tested, the model can be implemented to reengineer the original object.
What do you mean by Backpropagation in ANN?
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Answer: Backpropagation is the essence of neural network training. It is the method of fine-tuning the weights of a neural network based on the error rate obtained in the previous epoch (i.e., iteration). Proper tuning of the weights allows you to reduce error rates and make the model reliablRead more
Answer:
Backpropagation is the essence of neural network training. It is the method of fine-tuning the weights of a neural network based on the error rate obtained in the previous epoch (i.e., iteration). Proper tuning of the weights allows you to reduce error rates and make the model reliable by increasing its generalization.
Backpropagation in neural network is a short form for “backward propagation of errors.” It is a standard method of training artificial neural networks. This method helps calculate the gradient of a loss function with respect to all the weights in the network.
Back propagation algorithm:
The Back propagation algorithm in neural network computes the gradient of the loss function for a single weight by the chain rule. It efficiently computes one layer at a time, unlike a native direct computation. It computes the gradient, but it does not define how the gradient is used. It generalizes the computation in the delta rule.
Advantages of Backpropagation :
Most prominent advantages of Backpropagation are:
Types of Backpropagation :
Two Types of Backpropagation Networks are:
Static back-propagation:
It is one kind of backpropagation network which produces a mapping of a static input for static output. It is useful to solve static classification issues like optical character recognition.
Recurrent Backpropagation:
Recurrent Back propagation in data mining is fed forward until a fixed value is achieved. After that, the error is computed and propagated backward.
The main difference between both of these methods is: that the mapping is rapid in static back-propagation while it is nonstatic in recurrent backpropagation.
See lessList down the names of some popular Activation Functions used …
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See lessQuestion 1 List and explain different types of testing done …
Question 1 List and explain different types of testing done during the testing phase. Answer: Follow below link for answer: https://sikshapath.in/question/forward-engineering-is-not-necessary-if-an-existing-software-product/ Question 2 Analyze the role of testing tools in maintaining tRead more
Question 1
List and explain different types of testing done during the testing phase.
Answer:
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Question 2
Analyze the role of testing tools in maintaining the quality of software. Describe the mechanism to select testing tools for software
Answer:
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See lessFind the smaller number in an data array. Write 8085 …
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See lessHow software reverse engineering is helpful in development of software. …
The purpose of reverse-engineering is to find out how an object or system works. There are a variety of reasons to do this. Reverse-engineering can be used to learn how something works and to recreate the object or to create a similar object with added enhancements. Often the goal of reverse-engineeRead more
The purpose of reverse-engineering is to find out how an object or system works. There are a variety of reasons to do this. Reverse-engineering can be used to learn how something works and to recreate the object or to create a similar object with added enhancements.
Often the goal of reverse-engineering software or hardware is to find a way to create a similar product more inexpensively or because the original product is no longer available. Reverse-engineering in information technology is also used to address compatibility issues and make the hardware or software work with other hardware, software or operating systems that it wasn’t originally compatible with.
How does the reverse-engineering process work?
The reverse-engineering process is specific to the object on which its being performed. However, no matter the context, there are three general steps common to all reverse-engineering efforts. They include:
- Information extraction. The object being reverse-engineered is studied, information about its design is extracted and that information is examined to determine how the pieces fit together. In software reverse-engineering, this might require gathering source code and related design documents for study. It may also involve the use of tools, such as a disassembler to break apart the program into its constituent parts.
- Modeling. The collected information is abstracted into a conceptual model, with each piece of the model explaining its function in the overall structure. The purpose of this step is to take information specific to the original and abstract it into a general model that can be used to guide the design of new objects or systems. In software reverse-engineering this might take the form of a data flow diagram or a structure chart.
- Review. This involves reviewing the model and testing it in various scenarios to ensure it is a realistic abstraction of the original object or system. In software engineering this might take the form of software testing. Once it is tested, the model can be implemented to reengineer the original object.
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