Skip to main content

Deep Learning

 


                            Deep Learning




While Machine Learning is a subset of Artificial IntelligenceDeep Learning is a specialized subset of Machine Learning


Deep Learning layers algorithms to create a Neural Network, an artificial replication of the structure and functionality of the brain, enabling AI systems to continuously learn on the job and improve the quality and accuracy of results. This is what enables these systems to learn from unstructured data such as photos, videos, and audio files. Deep Learning, for example, enables natural language understanding capabilities of AI systems, and allows them to work out the context and intent of what is being conveyed. Deep learning algorithms do not directly map input to output. Instead, they rely on several layers of processing units. Each layer passes its output to the next layer, which processes it and passes it to the next. The many layers is why it’s called deep learning. 


When creating deep learning algorithms, developers and engineers configure the number of layers and the type of functions that connect the outputs of each layer to the inputs of the next. Then they train the model by providing it with lots of annotated examples. 


For instance, you give a deep learning algorithm thousands of images and labels that correspond to the content of each image. The algorithm will run the those examples through its layered neural network, and adjust the weights of the variables in each layer of the neural network to be able to detect the common patterns that define the images with similar labels. 



Deep Learning fixes one of the major problems present in older generations of learning algorithms. While the efficiency and performance of machine learning algorithms plateau as the datasets grow, deep learning algorithms continue to improve as they are fed more data. Deep Learning has proven to be very efficient at various tasks, including image captioning, voice recognition and transcription, facial recognition, medical imaging, and language translation. Deep Learning is also one of the main components of driverless cars.




Avinash C. Pillai

Technology Director

syniverse® 

The world’s most connected company™ 

Website / Twitter / LinkedIn/ connected company™  


Comments

Popular posts from this blog

Ephone Hunt Groups and Voice Hunt Groups Comparison

SIP phones support Voice Hunt Groups. SCCP phones support Ephone Hunt Groups, and in Cisco Unified CME 4.3 and later versions, SCCP phones also support Voice Hunt Groups.  Table 69  compares the features of Ephone Hunt Groups and Voice Hunt Groups. Table 69 Feature Comparison of Ephone Hunt Groups and Voice Hunt Groups Feature Ephone Hunt Voice Hunt Group Endpoints Supported SCCP only SIP, SCCP, PSTN, and FXS Parallel Hunt Groups (Call Blast) No (for alternative, see the  "Shared-Line Overlays" section ) Yes Hunt Statistics Support Yes No B-ACD Support Yes No Features such as present-call and login/logout Yes No Thanks & Regards Avinash Pillai URL :  http://avinashpillai.blogspot.com Email: avinashp25[AT]gmail[DOT]com

Seven Personal Qualities Found In A Good Leader

Whether in fact a person is born a leader or develops skills and abilities to become a leader is open for debate. There are some clear characteristics that are found in good leaders. These qualities can be developed or may be naturally part of their personality. Let us explore them further. Seven Personal Qualities Found In A Good Leader: 1. A good leader has an exemplary character. It is of utmost importance that a leader is trustworthy to lead others. A leader needs to be trusted and be known to live their life with honestly and integrity. A good leader “walks the talk” and in doing so earns the right to have responsibility for others. True authority is born from respect for the good character and trustworthiness of the person who leads.   2.A good leader is enthusiastic about their work or cause and also about their role as leader. People will respond more openly to a person of passion and dedication. Leaders need to be able to be a source of inspiration, and b...

What is Cybersecurity Risk? Definition & Factors to Consider

  Cybersecurity risk has become a leading priority for organizations as they embrace digital transformation and leverage advanced technology solutions to drive business growth and optimize efficiencies. Additionally, many organizations are increasingly reliant on third-party and   fourth-party vendors   or programs.  In this post, we’ll explore what cybersecurity risk is and take a look at some key cybersecurity risk factors that organizations across all industries should keep in mind as they build and refine their   cybersecurity risk management strategy .   What is cybersecurity risk? Cybersecurity risk refers to   potential threats and vulnerabilities   in digital systems. It encompasses the likelihood of a cyberattack compromising data or systems, leading to financial,   reputational , or operational damage. A few examples of cybersecurity risks include   ransomware ,   malware ,   insider threats ,   phishing attacks ...