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WHAT IS DEEP LEARNING?
Table Of Content What is Deep Learning?1 3 2 4 Example of Deep Learning. How does it work? Careers in deep learning. https://1stepgrow.com/course/advance-data-science-and-artificial-intelligence-course/
WHAT IS DEEP LEARNING?
Deep learning is a subset of machine learning where artificial neural networks, algorithms inspired by the human brain, learn from large amounts of data. Similarly to how we learn from experience, the deep learning algorithm would perform a task repeatedly, each time tweaking it a little to improve the outcome. We refer to 'deep learning' because the neural networks have various (deep) layers that enable learning. The amount of data
generate every day is staggering--currently
that
require an abundance of data to be able to learn from, this growth in data creation is the primary reason why the capabilities of deep learning have grown over the last few years.
Since deep learning
we
estimated at 2.6 quintillion bytes--and it's the resource
makes deep learning possible.
algorithms
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How does it work?
Deep Neural Networks have multiple layers of interconnected artificial neural neurons and nodes connected. Each of these nodes performs one simple mathematical purpose, typically an linear function that is responsible for the extraction and mapping of information. There are three layers to a deep neural network: the input layer, hidden layers, and the output layer. Data is fed to the layer of input.
Each node within the input layer takes in the data before passing it to the layer next, i.e. those hidden layers. The hidden layers are able to remove features from the input layer and transform it with the linear functions.
These layers are known as hidden layers since they are not able to determine the parameter (weights as well as biases) within each node are unidentified. These layers use random variables to alter data. Each produces different results.
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Example of Deep Learning
Virtual assistants
have
that
that
Driverless vehicles
that
Do you
Alexa, Cortana, or Siri? Virtual assistants
are popular use deep learning to learn the terms and languages
people use when they interact with them. This means that they are more proficient in providing the information required.
Automobiles
are autonomous have already appeared on the roads. Deep learning algorithms are able to identify whether the object that is on the roadway is actually a bag or another vehicle or a kid and act in a manner that is appropriate.
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Example of Deep Learning
Facial recognition
Medical science
Facial recognition plays a crucial function for everything, from tag individuals on social media to vital security measures. Deep learning permits algorithms to perform with precision despite changes in appearance like beards, hairstyles or even poor lighting.
Human genomes comprise around 3 billion DNA base pair of the chromosomes. The machine learning process is helping researchers and medical professionals , to create individualized medicines, detect cancer, and is currently undergoing studies and application for medical and pharmaceutical uses.
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Careers in deep learning In all aspects in machine-learning and AI, the careers that deal with deep learning have been expanding exponentially. Deep learning can provide companies and organizations systems the ability to make rapid progress that are complex and require a lot of explanation. Data Engineers specialize in deep learning and design the computational strategies needed by researchers to push the limits of the field. Data Engineers often work in particular areas of expertise and have a mix of abilities across different research projects.
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