Test (Objective Questions)
Geoinformatics Channel (Mitesh Sharma)
Geoinformatics Video (Direct Link)
Remote Sensing Video (Direct Link)
GIS Video (Direct Link)
Geoinformatics Playlist (Direct Link)
Deep Learning is an intense extension of Machine Learning
Blogger Name : Mitesh Sharma
Date & Time: 15August2019 & 09:30 PM
Deep Learning is an intense extension of Machine Learning. It is used to solve the complex problems. It works on both CPU and GPU processor and high performance machines. It handles an enormous amount of both structured and unstructured data to find the solution like human brain. If problem is so complex and requires a vast amount of data for solution then Deep Learning comes in a role instead of Machine Learning like Speech Reorganization and Number Plate Detection.
Deep Learning is a subset of Machine Learning that solves complex problems with the help of trained algorithms and artificial neural network.
It trains machine models with smart algorithms to simulate human like human decision making power. Deep Learning works like human brain. It uses artificial Neural Network which works same like human’s Biological Neural Network. Model uses there own decision ability like human and generates features automatically on which refined output will produce. Deep Learning model works on those problems where Machine Learning algorithms faces difficulties to solve. Disease Detection, Chatbots, Robot Navigation, Automate Translation, Music Composition are some examples of Deep Learning.
Deep Learning does feature extraction automatically from the input data with the help of its Artificial Neural Network. Deep Learning works on Artificial Neural Network mode.
Artificial Neural Network Model works on three layers:
1. Input layer
2. Hidden layer
3. Output layer
Model divides input data in to multiple parts in input layer. Every part has assigned random weight through different node and model performs a mathematical function in hidden layer to generate result and pass the processed result to output layer. If output is not similar to real output than model again perform the process with different weights and generate result. Data Scientist and Engineers detects the problem and solution manually in Machine Learning but in Deep Learning trained models detects and solves the problems automatically by Artificial Neural Network.
All the big giant companies like Google, Facebook, Amazon, Netflix, Uber and many more are using Deep Learning to make thier products more advance and secure. Google Translator convert text in any language with the help of Deep Learning. Facebook use it to recognize the face of users. Netflix use it to suggest movies to their customers according to their interest. Uber show the best shortest path to their customers. Amazon Alexa is an advance Artificial Intelligence example which also uses Deep Learning Model. Both Machine Learning and Deep Learning are used to achieve Artificial Intelligence and used according to problem complexity and data structure. With the help of them we can achieve Artificial Intelligence in our Machines and enable machine to mimic like human with the ability of decision making.
Deep Learning are used in following sectors:
Deep Learning operations:
Number Plate Detection
Live Examples of Deep Learning:
Tesla Self Driving Car
Facebook Face Recognization
Learn Geoinformatics, Remote Sensing, GIS:
Terms & Conditions