Which was the first deep neural network?
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Which was the first deep neural network?
LeNet5. It is the year 1994, and this is one of the very first convolutional neural networks, and what propelled the field of Deep Learning. This pioneering work by Yann LeCun was named LeNet5 after many previous successful iterations since they year 1988!
How do you start implementing a research paper?
Tips for Implementing Algorithms
- Read the whole paper. Read the whole paper, slowly.
- Devise a test problem.
- Optimize last.
- Understand the foundations.
What are the current and emerging research topics in the field of artificial neural networks?
Neural Network Projects
- Autoencoders based on neural networks.
- Convolutional neural network model.
- Recurrent neural network model.
- Cryptographic applications using artificial neural networks.
- Credit scoring system.
- Web-based training environment.
- Vehicle security system using facial recognition.
- Automatic music generation.
How do I write a research paper in machine learning?
State the goals of the research and the criteria by which readers should evaluate the approach. Categorize the paper in terms of some familiar class; e.g., a formal analysis, a description of some new learning algorithm, an application of established methods, or a computational model of human learning.
What is the idea behind the creation of artificial neural network?
The aim of Artificial Neural Networks is to realize a very simplified model of the human brain. In this way, Artificial Neural Networks try to learn tasks (to solve problems) mimicking the behavior of brain. The brain is composed by a large set of elements, specialized cells called neurons.
What started deep learning?
The history of Deep Learning can be traced back to 1943, when Walter Pitts and Warren McCulloch created a computer model based on the neural networks of the human brain. They used a combination of algorithms and mathematics they called “threshold logic” to mimic the thought process.