Top 20 Python Deep Learning Applications You Must Know
Deep Learning has become the most researched and prominent topic of data science. It is a subgroup of Machine Learning in Artificial Intelligence. It uses a hierarchical level of artificial neural networks to simulate human-like decisions. Artificial neurons function in a similar manner as the biological neuron of the brain works. It is capable of handling a large amount of unstructured data and extracting the relevant information in less time. It extends the walls of technology by achieving results that were not possible earlier. Industries are using Deep Learning for different tasks. Self- driving cars, chatbots, Google voice, and image recognition are a few examples of Deep Learning. In this article, you will learn about the riveting Deep Learning applications with Python.
Keeping you updated with latest technology trends, Join TechVidvan on Telegram
Real time Deep Learning Applications
Following are the applications of Deep Learning using Python:
1. Instant Visual Translation
With deep learning, identification of text on the images is possible. Once identification completes, it translates the text immediately and recreates the image with translated text.
For example, Suppose you visit an unknown country whose local language is not known to you. An app like google translator converts the text of an image in an understandable language.
2. Predicting the future
Deep neural network helps in the prediction of earthquakes, tsunamis, cyclones, etc. So that preventive measures can be taken to save lives from falling into the grasp of natural calamities.
With the help of deep learning Applications, chatbots are becoming smarter day by day. Amazon, Flipkart and many e-commerce websites are using chatbots for customer services. Transportation apps like Ola and Uber are also implementing chatbots to provide personalized aid. Siri is also a good example of a chatbot.
4. Medical Care
a) Deep learning helps in detecting cancer cells and analyzing the MRI images to give elaborative results.
b) Google has made Google AI eye doctor software. It examines retina scans and identifies diabetic retinopathy, which can cause blindness.
5. Music and Audio Generation
Google’s waveNet and Baidu’s deep speech instruct a computer to learn the pattern and statistics. It can generate a completely new composition of music with the help of deep learning.
6. Automatic Translation Machine
The technology behind the google translation is deep learning. The neural network translates the given word, phrase or sentence into another language. Text translation performs without any pre-processing of sequence. It allows an algorithm to study the protectorate between words and their mapping to a new language. A stacked network of huge neural networks performs these kinds of translations.
7. Self –Driving Cars
Google has made an amazing self-driven car. This car operates on a combination of sensors and software. Car can classify objects, people, traffic signs and signals. It also detects the road works. It uses lidar technology.
8. Colorizing the images
Deep learning makes it possible to color the black and white images. It uses convolutional neural network for the same.
9. Read lip movements
Using deep learning with python, oxford and google’s scientists developed a neural network known as lipnet. It can read people’s lips with 93% success.
10. Photo Descriptions
System tends to automatically classify photographs. Deep Learning has the capacity to narrate every existing element in the image. Deep learning networks can identify the captivating areas of the images and can describe them into the sentences.
11. Handwriting generation
This application involves the creation of a new set of handwriting for the collection of words or phrases. It learns the relationship between pen and letters and can generate new examples.
12. Deep Dreaming
It is a very interesting application of deep learning. As the name suggests, it allows the system hallucinates on the top of an image and generate the resembling dream. Dreams depend upon the type of neural network .
Deep learning has transformed the advertising field. Publishers and advertisers use deep learning to increase the relevancy of their ads. Deep learning makes it possible for publishers to leverage the content to create the real time bidding for the ads.
14. Pixel Restoration
Researchers of Google brain trained Deep Learning network to take low resolution images of faces and predict the face through it. This technique is known as Pixel Recursive Super Resolution. It increases the resolution of images notably,determining the important features just enough for the identification of a person.
15. Adding sounds to silent videos
This task can be performed using training 1000 videos that have drum sticks sound strikes on different surfaces and creates different sounds. Models use these videos to predict the best suited sound in the video.
16. Fraud Detection
Deep learning with python is also benefiting the bank and financial sector. One can detect fraud by identifying patterns in transactions and credit scores.
Python with deep learning makes it possible for entertainment mediums (Netflix and Amazon) to give the personalized experience to the users. They create user’s persona factors in show preferences, time of access, history, etc. and recommend the shows that the viewer likes.
18. Fraud News Detection
Anyone can encounter with the fake news in one way or another. It is now possible to filter out the bad news from the reader’s feed. Deep Learning helps in detecting fake or biased news and removes it from the reader’s feed.
19. Visual Recognition
It sorts out the photos based on the location detected in the images, combination of people, or depending on dates and events. Searching for a particular photograph from Google’s picture library needs state–of-the-art-visualization consisting of several layers varying from basic to advanced elements.
20. Virtual Assistants
It is one of the most interesting deep learning applications. Siri,Alexa, and Google Assistant are examples of virtual assistants. These virtual assistants rely on deep learning to understand its user and give them proper response naturally.
Python with Deep Learning has given a boom to technology. Python’s simplicity and Deep Learning’s ability to solve unstructured data has sought the attention of all the industries. Python’s easy syntax encourages new developers to test the complex algorithms of deep learning quickly.
Hence , the combination of python and Deep Learning is giving new wings to technology. In this article, you have read some of the best Python Deep Learning applications. Hope this article will help you to understand the applications clearly.
Now its your turn to implement them. Here is how you can Implement real Time Face Recognition using Python.