Machine Learning 101 – The Problem-Solution Paradigm

Deep Learning Algorithms

Machine Learning as a Neural Technology is directed towards creating and developing the abilities in machines to be smart enough to perform undefined tasks without having to be programmed specifically each time. Machine Learning is an algorithm that allows systems & machines to recognize patterns of repetitive processes in the existing data and then predict similar patterns in the new data and make decisions based on the actions taken previously.

Machine Learning Algorithm

AI experts in the early stages realized that rather than feeding all the information to computers and then carrying out tasks based on a predefined algorithm, it was possible to teach them to learn by themselves by making them analyze huge amounts of digital data available on the internet and programming them to replicate human brain-like thought processing ability.

In Machine Learning it is important for the experts to create a language or medium that is understood by the machines. An Artificial Neural Network (ANN) is an information processing paradigm that is influenced by the way biological nervous systems (human brain) function. In simpler words, its the process of feeding information to computers and programming them to be able to classify data just like the humans do by recognizing patterns and setting up feedback loops for different scenarios.

ML_era

Why use Neural Networks?
Neural systems, have the wonderful ability to extract relevant information from complex or corrupt information, can be utilized to segregate references and identify patterns that are too overwhelming to possibly be identified by humans or other computational methods.

A few advantages of Neural Networks are –

  1. Adaptive Learning: A capacity to figure out how to perform tasks in light of the information given as reference patterns.
  2. Self-Organisation: can make its own association or portrayal of the data it gets during the time of ‘learning’.
  3. Real-Time Operation: computations can be run parallel at the time of data feed, and gadgets are being designed that can exploit this capability.
  4. Fault Tolerance via Redundant Information Coding: the partial destruction of a system prompts the relative corruption of performance. Be that as it may, some system abilities might still be retained even after major system damage.

Machine Learning is the fastest growing technology in the field of Artificial Intelligence. Machine Learning is still in the early stages of commercial implementation but companies that have adopted the technology are already drawing the benefits. With Machine Learning organizations and technology, experts have to figure out the ‘problem-solution’ paradigm to unlock the best value out of Machine Learning & Artificial Intelligence.

Ace also aims to bridge the gap & bring the power of Machine Learning as a technology to the doorsteps of mainstream industries that are reinventing their organizational structure through growth acceleration and innovation. 

#MachineLearning#ML #NeuralNetworking #ArtificialNarrowIntelligence #ML&Ace #AdvancedTechnology #AceInfoway #Neuroscience

Arpit Trivedi
Arpit Trivedi
Arpit is an IT professional who believes in creating Strategic Partnerships through Technology Consulting. He is also a programmer, database developer, and a growth accelerator.