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What is Machine Learning?

What is Machine Learning?
Evolution of Machines
How does Machine Learning work?
What is Supervised Learning?
What is Unsupervised Learning?
What is Reinforcement Learning?
Machine Learning Use Cases
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Future of IT Industry

by stevemor97 In reply to What is Machine Learning?

Machine learning is one of the best thing in It industry. It is of two types Supervised and Non-Supervised learning.Machine learning is use to predict the future trends of business and market with various algorithm.
There are many algorithm
1 Linear regression
2 Classifical regression

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ML definition

by jeffreyrusch In reply to What is Machine Learning?

Machine learning (ML) is the scientific study of algorithms and statistical models that computer systems use to perform a specific task without using explicit instructions, relying on patterns and inference instead. It is seen as a subset of artificial intelligence. Machine learning algorithms build a mathematical model based on sample data, known as "training data", in order to make predictions or decisions without being explicitly programmed to perform the task. Machine learning algorithms are used in a wide variety of applications, such as email filtering and computer vision, where it is difficult or infeasible to develop a conventional algorithm for effectively performing the task.
from https://en.wikipedia.org/wiki/Machine_learning

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Machine learning

by deborasumopayroll In reply to What is Machine Learning?

Machine learning is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. Machine learning focuses on the development of computer programs that can access data and use it learn for themselves.
The process of learning begins with observations or data, such as examples, direct experience, or instruction, in order to look for patterns in data and make better decisions in the future based on the examples that we provide. The primary aim is to allow the computers learn automatically without human intervention or assistance and adjust actions accordingly.
Some machine learning methods
Machine learning algorithms are often categorized as supervised or unsupervised.
• Supervised machine learning algorithms can apply what has been learned in the past to new data using labeled examples to predict future events. Starting from the analysis of a known training dataset, the learning algorithm produces an inferred function to make predictions about the output values. The system is able to provide targets for any new input after sufficient training. The learning algorithm can also compare its output with the correct, intended output and find errors in order to modify the model accordingly.
• In contrast, unsupervised machine learning algorithms are used when the information used to train is neither classified nor labeled. Unsupervised learning studies how systems can infer a function to describe a hidden structure from unlabeled data. The system doesn’t figure out the right output, but it explores the data and can draw inferences from datasets to describe hidden structures from unlabeled data.
• Semi-supervised machine learning algorithms fall somewhere in between supervised and unsupervised learning, since they use both labeled and unlabeled data for training – typically a small amount of labeled data and a large amount of unlabeled data. The systems that use this method are able to considerably improve learning accuracy. Usually, semi-supervised learning is chosen when the acquired labeled data requires skilled and relevant resources in order to train it / learn from it. Otherwise, acquiring unlabeled data generally doesn’t require additional resources.
• Reinforcement machine learning algorithms is a learning method that interacts with its environment by producing actions and discovers errors or rewards. Trial and error search and delayed reward are the mo

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simple

by johnlee90 In reply to What is Machine Learning?
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Machine Learning

by gracehadid123 In reply to What is Machine Learning?

It is the scientific learning of statistical models and algorithms used to perform a specific task without any direct instructions relying on patterns.

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Machine Learning

by oliverzofia In reply to What is Machine Learning?

A subset of artificial intelligence where the scientific study of algorithms happens and helps the computer systems to perform special tasks without any explicit instructions. Also depends on patterns and inference.

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ML - Machine Learning

by AeriesATG In reply to What is Machine Learning?

Machine learning is the scientific study of algorithms and statistical models that computer systems use to perform a specific task without using explicit instructions, relying on patterns and inference instead. It is seen as a subset of artificial intelligence.

Read in details from Wikipedia : https://en.wikipedia.org/wiki/Machine_learning

link removed by moderator

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machine learning

by asthasage955 In reply to What is Machine Learning?

Machine learning refers to a kind of application of artificial intelligence which provides systems the capability to spontaneously learn and improve from happening without being explicitly programmed.

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Should We Engineer AI For Luxury or Utility?

by engineeringera In reply to machine learning

Machine Learning (ML) is a vast, deep, and thoroughly interesting topic - one that should be acknowledged as indifferent to the future of humanity. So far, what we have been presented as AI, are mostly examples of ML, in various degrees. That is unless you're talking about someone like SOPHIA the cyborg. She is a product of intensive algorithms in Deep Learning technology. Humanity has reached a stage where they can Engineer AI for a plethora of services - yet, as a whole, we cannot even assess the difference between ML, DL, and AI.
Tl;dr Humans who Engineer AI for luxury, as opposed to a utility, are mistaken to what the frankly interesting field is capable of providing.
~Engineer.AI

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Subset of AI

by pithwip In reply to What is Machine Learning?

ML is a combination of algorithms and statistical models to predict the results based on data or patterns. ML algorithms executes based on previous execution patterns. ML becomes vital in automation, real life example of ML is self driving car where the car learns to drive itself from previous driving patterns or a chatbot Google's Meena who responds as per supervised learning.

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