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Machine Learning Basics Everyone Should Know - InformationWeek


AI is seeping into just about everything, from consumer products to industrial equipment. As enterprises utilize AI to become more competitive, more of them are taking advantage of machine learning to accomplish more in less time, reduce costs and discover something whether a drug or a latent market desire. While there's no need for non-data scientists to understand how machine learning (ML) works, they should understand enough to use basic terminology correctly. Although the scope of ML extends considerably past what's possible to cover in this short article, following are some of the fundamentals. Before one can grasp machine learning concepts, they need to understand what machine learning terms mean.

The 8 Neural Network Architectures Machine Learning Researchers Need to Learn


Why do we need Machine Learning? Machine learning is needed for tasks that are too complex for humans to code directly. Some tasks are so complex that it is impractical, if not impossible, for humans to work out all of the nuances and code for them explicitly. So instead, we provide a large amount of data to a machine learning algorithm and let the algorithm work it out by exploring that data and searching for a model that will achieve what the programmers have set it out to achieve. Let's look at these 2 examples: Then comes the Machine Learning Approach: Instead of writing a program by hand for each specific task, we collect lots of examples that specify the correct output for a given input. A machine learning algorithm then takes these examples and produces a program that does the job.

What Is Deep Learning?


Deep learning is one of the most influential and fastest growing fields in artificial intelligence. However, getting an intuitive understanding of deep learning can be difficult because the term deep learning covers a variety of different algorithms and techniques. Deep learning is also a subdiscipline of machine learning in general, so it's important to understand what machine learning is in order to understand deep learning. Deep learning is an extension of some of the concepts originating from machine learning, so for that reason, let's take a minute to explain what machine learning is. Put simply, machine learning is a method of enabling computers to carry out specific tasks without explicitly coding every line of the algorithms used to accomplish those tasks.

How Neural Network Algorithms Works : An Overview Vinod Sharma's Blog


AILabPage defines – Artificial neural networks (ANNs) as "Biologically inspired computing code with the number of simple, highly interconnected processing elements for simulating (only an attempt) human brain working & to process information model".