General discussion

What is Machine Learning?

By simplivllc ·
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
7 total posts (Page 1 of 1)  
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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

by arsomartinera In reply to Future of IT Industry

"machine learning" and "neural networks" it's just buzz word, it's a lot bigger than that

Just for the theory side, I have an opinion on this, for me it is extremely indispensable and almost exclusively that, for people who make progress in the field, who do research, who must be creative and look for new results

After there is the data scientist who must understand a minimum how the algos they use (and still) work. it's mostly a process and methodologies the job of data scientist, but in fact he must especially know how and when to use this algo toolbox to process data, know how to interpret results etc.

And then, the last case, is people who just use toolboxes without trying to understand what it's behind or vaguely, but having learned what it takes as input and what it needs to converge at least.

The ratio theory / practice depends on the category in which you want to be, depending on the algorithmic categories you want to use.

In resources, there is a lot of MOOC on the known sites, and recently a book in French is output written by this woman

https://twitter.com/WiMLDS_Paris/status/1071012211903078400?s=19 https://emicalculator.org.in/ https://gstseva.co.in/gst-login/ https://ifsccode.gen.in/

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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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