Deep Learning With Python Tutorial For Beginners – DNN & ANN

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Today, we will see Deep Learning with Python Tutorial. Deep Learning, a Machine Learning method that has taken the world by awe with its capabilities. In this Python Deep Learning Tutorial, we will discuss the meaning of Deep Learning With Python. Also, we will learn why we call it Deep Learning. Moreover, this Python Deep learning Tutorial will go through artificial neural networks and Deep Neural Networks, along with deep learning applications.

Companies have seen improvements in many areas as Deep Learning allows systems to make significant progress and solve tasks that were previously thought of as difficult. This ability to train on enormous sets of data and select only pertinent features by itself will prove exceptionally valuable when tackled with challenging issues.

So, let’s start Deep Learning with Python.

Deep Learning With Python Tutorial For Beginners - 2018

Deep Learning With Python Tutorial For Beginners – 2018

What is Deep Learning with Python?

a. Deep Learning Definition

To define it in one sentence, we would say it is an approach to Machine Learning. To elaborate, Deep Learning is a method of Machine Learning that is based on learning data representations (or feature learning) instead of task-specific algorithms. We also call it deep structured learning or hierarchical learning, but mostly, Deep Learning.

For feature learning, we observe three kinds of learning- supervised, semi-supervised, or unsupervised.
The patterns we observe in biological nervous systems inspires vaguely the deep learning models that exist.

Another tremendous advantage of Deep Learning models is the ability to learn representations at multiple levels of abstraction, so the model can function well across different types of tasks. It is critical when designing models like image and speech recognition where feature extraction would be quite difficult if approached in the traditional manner.

b. Characteristics of Deep Learning With Python

Some characteristics of Python Deep Learning are-

  • They use a cascade of layers of nonlinear processing units to extract features and perform transformation; the output at one layer is the input to the next.
  • These learn in supervised and/or unsupervised ways (examples include classification and pattern analysis respectively).
  • These learn multiple levels of representations for different levels of abstraction.

Do you read Machine Learning With Python

Deep Learning With Python – Why Deep Learning?

Deep Learning uses networks where data transforms through a number of layers before producing the output. This is something we measure by a parameter often dubbed CAP. The Credit Assignment Path depth tells us a value one more than the number of hidden layers- for a feedforward neural network. But we can safely say that with Deep Learning, CAP>2. Each layer takes input and transforms it to make it only slightly more abstract and composite.

Deep Learning With Python – (ANN)

Now, let’s talk about neural networks. An Artificial Neural Network is a connectionist system. It is a computing system that, inspired by the biological neural networks from animal brains, learns from examples. When an ANN sees enough images of cats (and those of objects that aren’t cats), it learns to identify another image of a cat.

a. Structure

An Artificial Neural Network is nothing but a collection of artificial neurons that resemble biological ones. Synapses (connections between these neurons) transmit signals to each other. A postsynaptic neuron processes the signal it receives and signals the neurons connected to it further.
Have a look at Machine Learning vs Deep Learning

Deep Learning With Python

Deep Learning With Python – Structure of Artificial Neural Networks

A neuron can have state (a value between 0 and 1) and a weight that can increase or decrease the signal strength as the network learns. We see three kinds of layers- input, hidden, and output. There may be any number of hidden layers. Typically, such networks can hold around millions of units and connections. Note that this is still nothing compared to the number of neurons and connections in a human brain.

Deep Neural Networks

A Deep Neural Network is but an Artificial Neural Network with multiple layers between the input and the output. At each layer, the network calculates how probable each output is. A DNN will model complex non-linear relationships when it needs to. With extra layers, we can carry out the composition of features from lower layers.

Deep Learning With Python

Deep Neural Networks

Typically, a DNN is a feedforward network that observes the flow of data from input to output. It never loops back. Deep Neural Network creates a map of virtual neurons and assigns weights to the connections that hold them together. It multiplies the weights to the inputs to produce a value between 0 and 1. When it doesn’t accurately recognize a value, it adjusts the weights. This is to make parameters more influential with an ulterior motive to determine the correct mathematical manipulation so we can fully process the data.
Two kinds of ANNs we generally observe are-

  • Recurrent Neural Networks- Where data can flow in any direction. We use concepts like LSTM (Long Short-Term Memory) from these in areas like language modeling.
  • Convolutional Deep Neural Networks- A deep, feedforward ANN. We use these in areas like analyzing visual imagery, computer vision, and acoustic modeling for ASR (Automatic Speech Recognition)

Deep Learning With Python – Deep Learning Applications

We observe the use of Deep Learning with Python in the following fields-

  • Automatic speech recognition.
  • Image recognition.
  • Visual art processing.
  • Natural Language Processing (NLP).
  • Drug discovery and toxicology.
  • Customer Relationship Management (CRM).
  • Recommendation systems.
  • Bioinformatics.
  • Mobile advertising.
  • Image Restoration.
  • Financial fraud detection.

For more applications, refer to 20 Interesting Applications of Deep Learning with Python.
Before we bid you goodbye, we’d like to introduce you to Samantha, an AI from the movie Her.

Deep Learning With Python

Deep Learning With Python tutorial

In the film, Theodore, a sensitive and shy man writes personal letters for others to make a living. Samantha is an OS on his phone that Theodore develops a fantasy for. What starts with a friendship takes the form of love.

Deep Learning With Python

Will deep learning get us from Siri to Samantha in real life? Well, at least Siri disapproves.

Deep Learning With Python

So, this was all in Deep Learning with Python tutorial. Hope you like our explanation.

Conclusion

Hence, in this Tutorial, we discussed what exactly deep learning with Python means. Also, we saw artificial neural networks and deep neural networks in Deep Learning With Python Tutorial. Moreover, we discussed deep learning application and got the reason why Deep Learning. See you again with another tutorial on Deep Learning. Furthermore, if you have any query, ask in the comment tab.
See also –
Learning rules in Neural Network
For reference

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DataFlair Team

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