What is "MACHINE LEARNING " IN Hindi & English .(मशीन लर्निंग क्या है?)
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Do you know what is Machine Learning? It sounds very technical in hearing. But if you understand about it properly then it is a very easy funda which is nowadays used in all places. This is a kind of learning in which Machok learns a lot of things without being explicitly programmed. This is a type of application that AI (Artificial Intelligence) gives the system the ability to automatically learn from your own experience and improve yourself.
Machine learning is primarily a process in which machines like computers learn things automatically. In this scheme machines learn the same things as the human brain and in the process they do not need any human help.
Machine learning is an algorithm that helps in running the software properly, and it is used to predict Outlook without predicting any programming.
The general work of machine learning is that it creates such algorithm so that it can take input data and can easily perform statistical analysis. So that he could tell the data coming out of the output and update the new data.
The process that takes place in data mining and predictive modeling is the same as machine learning. In both the data is searched in the first pattern, then it is applied according to the program.
A lot of people are aware of machine learning because many people do online shopping from the internet and those who see the swinging Ed with shopping, also walk with the help of machine learning.
There are also some search engines in online ad deliveries who also use machine learning. Apart from this kind of marketing, machines are also used in cases such as fraud, spam filtering, threshold detection and network security.
We split the machine learning algorithm into Supervised and Unsupervised. In order to create a supercycled algorithm, we need data scientist and data analyst, which comes with machine learning that can tell all the output and input, it also tells acrease and feedback too. The data scientist tells us which variable and feature we should use for development.
2.
Unsurceptible algorithm does not require any training for any outcome data. The reason is that it uses an interactive approach that we speak deep learning. We also call the Nuclear Networks Algorithm, and it works in Complex Processing Tasks. Such as image rectification, speech to text, and natural language generation. Such neural networks compile Milianus training data automatically and make co-relationships in the variable.
There are also some search engines in online ad deliveries who also use machine learning. Apart from this kind of marketing, machines are also used in cases such as fraud, spam filtering, threshold detection and network security.
मशीन लर्निंग कैसे काम करता है? (function of machine learning in hindi)
2.
Unsurceptible algorithm does not require any training for any outcome data. The reason is that it uses an interactive approach that we speak deep learning. We also call the Nuclear Networks Algorithm, and it works in Complex Processing Tasks. Such as image rectification, speech to text, and natural language generation. Such neural networks compile Milianus training data automatically and make co-relationships in the variable.
मशीन लर्निंग कृत्रिम बुद्धिमत्ता (एआई) का एक अनुप्रयोग है जो सिस्टम को स्पष्ट रूप से प्रोग्राम किए बिना अनुभव से स्वचालित रूप से सीखने और सुधारने की क्षमता प्रदान करता है। मशीन लर्निंग उन कंप्यूटर प्रोग्राम्स के विकास पर ध्यान केंद्रित करता है जो डेटा तक पहुँच सकते हैं और इसे अपने लिए सीख सकते हैं।
सीखने की प्रक्रिया टिप्पणियों या डेटा से शुरू होती है, जैसे कि उदाहरण, प्रत्यक्ष अनुभव, या निर्देश, ताकि डेटा में पैटर्न की खोज हो सके और हम जो उदाहरण प्रदान करते हैं, उसके आधार पर भविष्य में बेहतर निर्णय ले सकें। प्राथमिक उद्देश्य कंप्यूटर को मानवीय हस्तक्षेप या सहायता के बिना स्वचालित रूप से सीखने और तदनुसार कार्यों को समायोजित करने की अनुमति देना है।
मशीन कैसे सीखते हैं?मशीन लर्निंग एल्गोरिदम
सुपरवाइज्ड मशीन लर्निंग एल्गोरिदम
भविष्य के घटनाओं की भविष्यवाणी करने के लिए लेबल किए गए उदाहरणों का उपयोग करके नए डेटा के लिए अतीत में जो सीखा गया है, उसे लागू कर सकता है। एक ज्ञात प्रशिक्षण डेटासेट के विश्लेषण से शुरू होकर, सीखने का एल्गोरिथ्म आउटपुट मानों के बारे में भविष्यवाणियां करने के लिए एक अनुमानित कार्य करता है। सिस्टम पर्याप्त प्रशिक्षण के बाद किसी भी नए इनपुट के लिए लक्ष्य प्रदान करने में सक्षम है। लर्निंग एल्गोरिथ्म इसके आउटपुट की सही, इच्छित आउटपुट के साथ तुलना कर सकता है और तदनुसार मॉडल को संशोधित करने के लिए त्रुटियों का पता लगा सकता है।
इसके विपरीत, अप्रशिक्षित मशीन लर्निंग एल्गोरिदम का उपयोग तब किया जाता है जब ट्रेन में उपयोग की जाने वाली जानकारी को न तो वर्गीकृत किया जाता है और न ही लेबल किया जाता है। अनसेफाइरेटेड लर्निंग स्टडीज कैसे सिस्टम अनलिस्टेड डेटा से एक छिपे हुए ढांचे का वर्णन करने के लिए एक फ़ंक्शन का अनुमान लगा सकता है। सिस्टम सही आउटपुट का पता नहीं लगाता है, लेकिन यह डेटा की पड़ताल करता है और डेटा से अनलिस्टेड डेटा से छिपे हुए स्ट्रक्चर्स का वर्णन करने के लिए इनसेट्स को आकर्षित कर सकता है।
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aprendizaje
artificial
datos
deep
deeplearning
leainteligencia
machine learning vs deep learning vs artificial intelligence
network
neural
neuronales
profundo
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