Dear B.K. Tripathy

While Neural Networks use neurons to transmit data in the form of input values and output values through connections, Deep Learning is associated with the transformation and extraction of feature which attempts to establish a relationship between stimuli and associated neural responses present in the brain

Kind Regards

Qamar Ul Islam

Hi B.K. Tripathy,

you can find the following link for your reference

https://serokell.io/blog/deep-learning-and-neural-network-guide

Dear Munuswamy,

Thanks for the link. It says that not all neural networks are deep. However, towards the end under conclusion it is said that "Neural networks are just one type of deep learning architecture". So, it is difficult to make out anything.

Can we conclude that Deep learning and Neural network have an intersection, but these two fields have distinct components beyond this intersection?

By comparing test accuracy, the training time of model and recognition time required for classifying new images.

B.K. Tripathy Neural network and deep learning is same things. In neural network the node and depth of network is shallow( one hidden layer) but deep learning is advance neural network and has many hidden layers and multi input and output layer.

Deep learning is a subfield of machine learning, and neural networks make up the backbone of deep learning algorithms. In fact, it is the number of node layers, or depth, of neural networks that distinguishes a single neural network from a deep learning algorithm, which must have more than three. https://www.ibm.com/cloud/blog/ai-vs-machine-learning-vs-deep-learning-vs-neural-networks

Check

Deep Learning Vs Neural Networks – What’s The Difference? https://bernardmarr.com/deep-learning-vs-neural-networks-whats-the-difference/

CNN can be used to reduce the number of parameters we need to train without sacrificing performance — the power of combining signal processing and deep learning! But training is a wee bit slower than it is for DNN. LSTM required more parameters than CNN, but only about half of DNN. Deep is more like a marketing term to make something sounds more professional than otherwise. CNN is a type of deep neural network, and there are many other types. CNNs are popular because they have very useful applications to image recognition. https://stats.stackexchange.com/questions/234891/what-is-the-difference-between-convolutional-neural-networks-and-deep-learning

https://towardsdatascience.com/a-comparison-of-dnn-cnn-and-lstm-using-tf-keras-2191f8c77bbe

Deep learning is a set of learning methods attempting to model data with complex architectures combining different non-linear transformations. The elementary bricks of deep learning are the neural networks, that are combined to form the deep neural networks

Dear All,

Thanks for responding to my query. I have the following diagram in connection with this question. I would everyone to react whether the classification is correct. Any suggestions with logic or reference material for it will be appreciated. Please look into the attached file.

Dear B.K. Tripathy

I think the following papers can help you

Article Wind Speed Ensemble Forecasting Based on Deep Learning Using...

Article Advanced Ensemble Model for Solar Radiation Forecasting Usin...

Article Novel Feature Selection and Voting Classifier Algorithms for...

Dear Tripathy

Deep learning (DL) is a family of machine learning methods capable of detecting multiple levels of latent representations from the data. This is achieved by combining consecutive layers of simple nonlinear transformations that allow the extraction of increasingly abstract features. DL has become one of the most popular and promising approaches in machine learning.

Neural networks are a family of machine learning models that consist of connected function units called neurons. They are built as powerful function approximators that accurately map input data x to output y (i.e., to learn a function f(x) ≈ y) through multiple layers of nonlinear transformations. Such a design enables neural networks to perform tasks like classification and regression.

I strongly recommend the following links

Deep Neural Networks (DNN)

September 2021,DOI:10.1007/978-3-030-82184-5_4,In book: Introduction to Deep Learning for Healthcare

and

A Survey on Deep Leaning Architectures and Its Applications, January 2020DOI:10.26697/ijes.2020.4.2

GOOD LUCK