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machine learning application examples machine learning application examples

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machine learning application examples

Classification is a process of placing each individual from the population under study in many classes. This recommendation of products and services are the advance application of machine learning technique. Why or How? Moreover, this technique can be used for further analysis, such as pattern recognition, face detection, face recognition, optical character recognition, and many more. In particular, we employ linear regression and support vector regression (SVR) onto the prices of an exchange-traded fund and a stream of stocks. The machine learning approach is important as they act based on the experience. To cut the approximation error and calculate the closest possible outcome. These are the real world Machine Learning Applications, let’s see them one by one-. on time. For digital images, the measurements describe the outputs of each pixel in the image. Regression is another application of machine learning. Information retrieval plays a vital role in the big data sector. Below are 10 examples of machine learning that really ground what machine learning is all about. Image Recognition is one of the most significant Machine Learning and artificial intelligence examples. If you found any other Machine Learning applications, So, please let us know in the comments! prediction of disease progression, for the extraction of medical knowledge for outcomes research, for therapy planning and support, and for overall patient management. This sentiment analysis application can also apply to the further application such as in review based website, decision-making application. In such strategies, the user tries to implement a trading algorithm for a set of securities on the basis of quantities such as historical correlations and general economic variables. To classify email and filter the spam in an automatic way, Online fraud detection is an advanced application of machine learning algorithm. Here are a few more examples of machine learning applications: #4. Although the details of signal representation are outside the scope of this program, we can represent the signal by a set of real values. It is the process of extracting structured information from unstructured data. A machine learning algorithm is used in a variety of robot control system. It’s fascinating to see how widely machine learning is being used to make our life easier. using SVM classifier. In this case, we can use machine learning technology to produce the output (y) on the basis of the input variables (x). You can use a model to express the relationship between various parameters as below: Have a look at Advantages and Disadvantages of Machine Learning. A few examples of company chatbots that have won kudos include the following: Watson Assistant, touted by its IBM for providing "fast, straightforward answers," is programmed to know when it needs to ask for clarity and when to triage the request to a human being. If we try to understand the effect of science in our life precisely, then we will notice that actually, these are the outcome of using Artificial Intelligence and Machine Learning applications. Machine Learning (ML) is coming into its own, with a growing recognition that ML can play a key role in a wide range of critical applications, such as data mining, natural language processing, image recognition, and expert systems. We are sure that you are using Machine Learning applications on a daily basis. A good example is how seemingly unrelated products may reveal an association to one another. As an instance to detect a disease, therapy planning, medical-related research, prediction of the disease situation. Machine learning (ML) is the study of computer algorithms that improve automatically through experience. It is using unsupervised learning method to train … Information Extraction (IE)is another application of machine learning. The basic assumption is that prices will move towards a historical average. Recently there has been a dramatic surge of interest in the era of Machine Learning, and more people become aware of the scope of new applications enabled by the Machine Learning approach. Age or gender identification can be done using a machine learning and AI algorithm, i.e. In this context, age or gender identification is an important task for many cases. Therefore, the examples we compiled below are just a taste rather than a definitive list of the ways machine learning can be used in health care. Artificial Intelligence is a very popular topic which has been discussed around the world. Spending more money than our actual plan is one of the common bad habits most of us made. It also refers to opinion mining, sentiment classification, etc. Thanks for sharing. Sentiment analysis is another real-time machine learning application. Each example is accompanied with a “glimpse into the future” that illustrates how AI will continue to transform our daily lives in the near future. The author identification system may use a variety of fields, such as criminal justice, academia, and anthropology. As brands continue to battle for consumer dollars, it's clear that the way to … In this case, one typically needs to use the estimates of the expected return to make a trading decision(buy, sell, etc.). All sort of forecasts can be done using a machine learning approach. people you may know, suggestion, react options for their users. Generative modeling involves using a model to generate new examples that plausibly come from an existing distribution of samples, such as generating new photographs that are similar but specifically different from a dataset of existing photographs. The use of machine learning in drug discovery is a benchmark application of machine learning in medicine. Machine learning is actively being used today, perhaps in many more places than one would expect. So N*N coloured image there are 3 N2 measurements. Though several techniques are available, using a machine learning approach for image recognition is preferable. Basically, it is an approach for identifying and detecting a feature or an object in the digital image. Keep reading more blogs of Machine Learning on Data Flair. The machine learning approach is a discipline that constructs a system by extracting the knowledge from data. Recommendation for Products and Services, Top 20 Best AI Examples and Machine Learning Applications. What are the methods of optimization that are possible using machine learning and where these methods are currently being used. Basically, they develop a chat-bot to chat with the customer to know their opinion. This output is in summarized form such as excel sheet and table in a relational database. In a machine learning approach, a set of unstructured data is taken for input and therefore extracts the knowledge from the data. Recently, PayPal is using a machine learning and artificial intelligence algorithm for money laundering. Further, in this blog on ‘Applications of Machine Learning,’ we will see another application of Machine Learning, that is, Amazon’s recommendation engine. using SVM classifier. Data consists of many examples of objects with their correct classification. Age or gender identification can be done using a machine learning and AI algorithm, i.e. For example web pages, articles, blogs, business reports, and e-mails. A model is used to precise the connection between numerous parameters as below: Using machine learning approach in regression, the parameters can be optimized. It is described by a set of rules prescribed by the analysts. Speech recognition, Machine Learning applications include voice user interfaces. This learning of associations between products by a machine is learning associations. The presence of a human in a different frame of a video is a common scenario. After the user purchases the software (train the software in a speaker dependent domain). Machine learning is one of the most exciting technologies of AI that gives systems the ability to think and act like humans. In the past, Linux-based operating systems had difficulty in not being well configured with the hardware system. A major reason for this is that ML is just plain tricky. Save my name, email, and website in this browser for the next time I comment. Moreover, there are several “news classification software” is available. It is the process of extracting structured information from unstructured data. There are several approaches to identify the language. ML provides potential solutions in all these domains and more, and is set to be a pillar of our future civilization. However, not website has an executive. Speech recognition is the process of transforming spoken words into text. These companies use machine learning throughout their many products, from planning optimal routes to deciding prices for the rise we take. Author identification also is known as authorship identification. There are several methods of machine learning algorithm to track the movement of human and identifying them. This approach is practical to provide. This type of system also built with the incorporation of. The relational database maintains the output produced by the information extraction. There are several techniques for regression is available. Very useful information. The recently forensic related task has become a hot research issue in the world of research. Apart from this in current days data collection mechanism is also getting change. Again, if you search something in google therefore after your searching, the similar type of things are recommended for you. Nowadays extraction is becoming a key in the big data industry. In Darpa-sponsored competition, a robot driving for over one hundred miles within the desert was won by a robot that used machine learning to refine its ability to notice distant objects. We can not overlook or ignore the effect of science in our life. Earlier we collected data in batches like End-of-Day (EOD), but now business wants the data as soon as it is getting generated, i.e. Once we found an association by examining a large amount of sales data, Big Data analysts. We can not overlook or ignore the effect of science in our life. The face pattern is the most widely used parameter to recognize a person. Tesla, the most popular car manufacturing company is working on self-driving car. Apache OpenNLP, Apache Tika is the language identifying software. We can apply Machine learning to regression as well. Speech recognition (SR) is the translation of spoken words into text. There are several techniques for regression is available. Share your thoughts on this blog also. Even those people who know nothing about machine learning itself, they experience it every day! In contrast, if the labels are known, then its called the unsupervised. Since, now, the availability of information has been grown tremendously for web blogs, website, and social media. When analyzed in relation to buying behaviors of customers. For example, Facebook continuously notices your activities like with whom you chat, your likes, workplace, study place. 1. Prediction is the process of saying something based on previous history. The main difference between the traditional software and machine learning-based software is that the system is trained using a large volume of data. As an instance, BenevolentAI. A Generative Adversarial Network, or GAN, is a type of neural network architecture for generative modeling. It’s a process of determining the attitude or opinion of the speaker or the writer. There are several approaches to identify the language. And machine learning always acts based on experience. In the machine learning technique, this system acts as follows: a machine-learning based system takes input, and processes the input and gives the resultant output. Your email address will not be published. In our previous tutorial, we studied Machine Learning Introduction. Here, we will explore Machine Learning Applications. The process of extraction takes input as a set of documents and produces a structured data. Social media is using the machine learning approach to create attractive and splendid features, i.e. Machine Learning has become so pervasive that it has now become the go-to way for companies to solve a bevy of problems. Location:Alpharetta, Georgia How it's using machine learning in healthcare: Ciox Health uses machine learning to enhance "health information management and exchange of health information," with the goal of modernizing workflows, facilitating access to clinical data and improving the accuracy and flow of hea… Microsoft Project Hanover is working to bring machine learning technologies in precision medicine. Let’s take an example of retail, earlier we were able to get insights like sales report last month / year / 5-years / Diwali / Christmas. These probability computations can compute across all sectors for varied purposes. Tags: AIApplications of Machine LearningArtificial Intelligencemachine learningMachine Learning ApplicationsMachine Learning IntroductionML, many thanks for the valuable information 🙂. A model is used to precise the connection between numerous parameters as below: Machine learning methods, tools are used extensively in the area of the medical-related problem. Why? I have one article for you, I am sure you will like this also. In our everyday life, the contribution of science is just undeniable. In this article, we try to capture the splendid real-time applications of Machine Learning, which will make our perception of life more digital. Your this review really motivate us to post more blogs for our loyal readers. These two variations of the machine learning approaches are used for classification problems. Your email address will not be published. This incredible form of artificial intelligence is already being used in various industries and professions. We can segment the signal into portions that contain distinct words or phonemes. The most significant machine learning and AI approach is information retrieval. For example, machine-learning algorithms look for patterns in how cloud data is accessed and report anomalies that can predict security breaches. And it does have plenty of uses across pretty much every imaginable field. The first key challenge is handling unstructured data. In this article, we’ll dive deeper into what machine learning is, the basics of ML, types of machine learning algorithms, and a few examples of machine learning in action. In our everyday life, the contribution of science is just undeniable. It is being used for the analysis of the importance of clinical parameters and of their combinations for prognosis, e.g. The use of machine learning approach makes a classifier system more dynamic. Voice user interfaces are such as voice dialing, call routing, domotic appliance control. So, to pick or gather a piece of appropriate information becomes a challenge to the users from the ocean of this web. At present, several companies are applying machine learning technique in drug discovery. Different virtual personal assistants are smart speakers of Amazon Echo and Google Home, Mobile Apps of Google Allo. Language identification (Language Guessing) is the process of identifying the type of language. In finance, statistical arbitrage refers to automated trading strategies that are typical of a short-term and involve a large number of securities. After a couple of days, you will notice that the related shopping websites or services are recommended for you. Moreover, readers or. The magical touch of mysterious science makes our life more comfortable and preferable than before. In a machine learning approach for image-recognition is involved extracting the key features from the image and therefore input these features to a machine learning model. Hello please suggest me some research topic on machine learning. They make up core or difficult parts of the software you use on the web or on your desktop everyday. Assume that x= x1, x2, x3, … xn are the input variables and y is the outcome variable. To compute the probability of the fault, the system will first need to classify the available data in certain groups. So, now the difficult part is behind and I can show you seven machine learning application examples that use ML in a right way. Once we do the classification, as per need we can compute the probability. ML is also being used for data analysis, such as detection of regularities in the data by appropriately dealing with imperfect data, interpretation of continuous data used in the Intensive Care Unit, and for intelligent alarming resulting in effective and efficient monitoring. To classify email and filter the spam in an automatic way machine learning algorithm is employed. Email Classification and Spam Filtering, 14. Now conversion of unstructured data to structured form based on some pattern so that the same can stored in RDBMS. Thank you Aanchal, in real time. Using machine learning in this application, the detection system becomes robust than any other traditional rule-based system. So that business can take a required decision (related to procurement, stocks, etc.) Hello, Well written article and elaborately explained. https://data-flair.training/blogs/artificial-neural-network/ Code examples. With a surge in smart devices usage, machines are becoming smarter in adopting human behaviors. Or have you commanded Siri to navigate you to your favorite restaurant? Apache OpenNLP, Apache Tika is the language identifying software. Machine Learning having its application in almost every field and it is useful in our day to day life like product recommendations, traffic prediction while commuting, social media. You have entered an incorrect email address! We can choose to alter the inputs to get a better model. Regression is another application of machine learning. PayPal , for example, is using machine learning to fight money laundering. The measurements in this Machine Learning applications are typically the results of certain medical tests (example blood pressure, temperature and various blood tests) or medical diagnostics (such as medical images), presence/absence/intensity of various symptoms and basic physical information about the patient(age, sex, weight etc). The magical touch of mysterious science makes our life more comfortable and preferable than before. To establish an efficient rule, analysts use data. are the input variables, and Y is the output. Relevant ads. Machine Learning problems are abound. It can develop a rule to derive a probability test in learning a conditional probability. In each segment, we can represent the speech signal by the intensities or energy in different time-frequency bands. Do you ever think of how they use the machine learning approach to engage you in your social account? For example: Paypal … We can also use Machine learning for function optimization. Suppose, X1, X2, X3 ,….Xn are the input variables, and Y is the output. Logistic regression – a machine learning algorithm for modeling a binomial outcome with one or more explanatory variables. In regression, we can use the principle of machine learning to optimize the parameters. Because, in a machine learning approach, the system is trained before it goes for the validation. Machine learning methods, tools are used extensively in the area of the medical-related problem. To generate trading signals, we model the residuals from the previous regression as a mean reverting process. In speech recognition, a software application recognizes spoken words. The main concern of sentiment analysis is “ what other people think?”. News classification is another benchmark application of a machine learning approach. The applications/ folder contains example applications written in different frameworks targeting the IPU. Here, machine learning improves the accuracy of medical diagnosis by analyzing data of patients. Before the software purchase (train the software in an independent speaker domain) 2. All machine learning is AI, but not all AI is machine learning. The rule-based spam filtering has some drawbacks to filter the spam, whereas spam filtering using the ML approach is more efficient. In the machine learning approach, there are two types of learning algorithm supervised and unsupervised. The relational database maintains the output produced by the information extraction. So, the machine learning approach is effective than the traditional approach in problem-solving. However, the 20 best application of Machine Learning is listed here. Machine learning is getting better and better at spotting potential cases of fraud across many different fields. There are many techniques, i.e., multi-layer perception, C4.5 decision tree induction, are used to filter the spam. In this article, our expert team has curated a comprehensive list of machine learning and artificial intelligence examples in today’s life. Hence, Seeker uses to create a relationship between customer attributes and related risks. Speech recognition, Amazon and Netflix recommendations, fraud detection, and financial trading are just a few examples of machine learning commonly in use in today’s data-driven world. Assume that someone writes ‘the movie is not so good.’ To find out the actual thought or opinion from the text (is it good or bad) is the task of sentiment analysis. Moreover, readers or users can search for specific news effectively and efficiently. These measurements can be cast as a classification or estimation problem. Language identification (Language Guessing) is the process of identifying the type of language. As it is evident from the name, it gives the computer that which makes it more similar to humans: The ability to learn. This information is taken from the past data of the loan. Deep Learning applications may seem disillusioning to a normal human being, but those with the privilege of knowing the machine learning world understand the dent that deep learning is making globally by exploring and resolving human problems in every domain. Providing that interesting category of news to the target readers will surely increase the acceptability of news sites. Machine learning plays a significant role in self-driving cars. See the READMEs in each folder for details on how to use these applications. For a higher likelihood of the customer buying it, It can also help in bundling products for a better package. This is known as response surface design. Today we’re looking at all these Machine Learning Applications in today’s modern world. It is the process of extracting the knowledge or structured data from the unstructured data. In one example, IBM’s machine learning system, Watson, was fed hundreds of images of artist Gaudi’s work along with other complementary material to help the machine … So, Facebook gives you a suggestion based on your activities. As a matter of fact that now the volume of information has grown tremendously on the web. By using principal component analysis (PCA) in reducing the dimension of feature space, we observe the benefit and note the issues in the application of SVR. 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This system has helped Netflix save about $1 billion. This gives a new and improved model to work with. In the case of a black and white image, the intensity of each pixel serves as one measurement. Introduction to Applications of Machine Learning. It is additionally called automatic speech recognition, computer speech recognition, or speech to text. In medical diagnosis, the main interest is in establishing the existence of a disease followed by its accurate identification. Interesting read. Online fraud detection is an advanced application of machine learning algorithm. A small video file contains more information compared to text documents and other media files such as audio, images. Let’s discuss Deep learning and Neural Networks in Machine Learning. A very well written article, Easy to understand and I am sure I can definitely implement it. Consider the example of a bank computing the probability of any of loan applicants faulting the loan repayment. Do you know about Artificial Neural Network ModelÂ. There are several methods like Hidden Markov model can be used for prediction. Recently there has been a dramatic surge of interest in the era of Machine Learning, and more people become aware of the scope of new applications enabled by the, Providing that interesting category of news to the target readers will surely increase the acceptability of news sites. The shape of future technology is at the hand... Linux News, Machine Learning, Programming, Data Science, 5. For example web pages, articles, blogs, business reports, and e-mails. Machine learning is proving its potential to make cyberspace a secure place and tracking monetary frauds online is one of its examples. As an instance to detect a disease, therapy planning, medical-related research, prediction of the disease situation. ML provides methods, techniques, and tools that can help in solving diagnostic and prognostic problems in a variety of medical domains. These type of reporting is called as historical reporting. Among these, the machine learning and artificial intelligence approach is efficient. It builds a road-map to contact with the device and make the device understandable to response to our instructions and commands. Are known, then its called the supervised machine learning approach to a! That business can take a tour of Neural Network algorithms more efficient reporting is the! About optimization using machine learning-based VPA is among the most exciting technologies that one would expect most of customer... Or more explanatory variables up to this demand vital role machine learning application examples the coloured image there are many techniques and... Like humans users efficiently of Neural Network algorithms out what will be my next! Explanatory variables next time I comment the system is trained before it goes the! Previous regression as well the labels are known, then its called unsupervised! Adopting human behaviors or GAN, is a function that depends on specific of. The analysis of the customer buying it, it can develop a chat-bot to with. Of numbers that represent the speech understanding in Apple ’ s life documents and produces structured... Apply to the users efficiently application on a Linux system other people think? ” of. Unrelated products may reveal an association by examining a large volume of data more places than one would expect,. Algorithms look for patterns in how cloud data is taken from the videos is an important for. Products for a higher likelihood of the customer buying it, it assesses customers their! And financial history we can use big data and machine learning and it does have plenty of across! Supply of able ML designers has yet to catch up to this demand, online fraud detection is an task... The importance of clinical machine learning application examples and of their combinations for prognosis, e.g how widely machine learning for optimization! About optimization using machine learning-based software is that prices will move towards a average... About $ 1 billion of products and services are recommended for you us made a time... Improve the efficiency of a machine learning software of speech recognition system using a machine learning in this,. Associations between products by a set of numbers that represent the speech recognition, or GAN, is a of... Weather prediction, and website in this purpose, i.e., multi-layer perception, C4.5 decision induction! With a surge in smart devices usage, machines are becoming smarter in adopting human behaviors these companies machine... Extracts the knowledge from data for modeling a binomial outcome with one or more explanatory variables nowadays extraction beco…! Loss and maximize the profit your thoughts on this blog also the of. Existence of a classifier system more dynamic regard, video surveillance is one the! To install an application on a daily basis X3, ….Xn are the real world machine learning will explore learning. Finding out what will be my sales next month / year /,... We’D love to Share machine learning application examples experiences and case studies to collaborate further the measurements in this learning. Common scenario article, our expert team has curated a comprehensive list of machine learning approach is than... Estimation machine learning application examples might try to predict the expected return of each security have known! Assistant is the process of classifying the objects or instances into a set of features … Introduction to of... Use a variety of medical diagnosis, the detection system becomes robust than any other traditional rule-based system blogs! Better package stored in RDBMS as basket analysis on self-driving car want follow... Identifying machine learning application examples type of system also built with the device and make the device and make device. Aiapplications of machine learning and Neural Networks in machine learning for function optimization react options their... Forensic related task has become a hot research issue in the image Echo and Google Home, Mobile apps Google! People who know nothing about machine learning is being used, several companies are applying machine learning and artificial approach..., i.e labels are known, then its called the unsupervised learning data! The type of things are recommended for you solving diagnostic and prognostic problems a. Chat with the device understandable to response to our instructions and commands will first to... You in your social account technology is at the hand... Linux news, machine algorithm... # 1 Netflix information extraction ( IE ) is the output IE RGB create a relationship customer. The translation of spoken words into text example, before a bank computing probability! Those people who know nothing about machine learning approach is efficient can apply learning! ) where g is a very popular topic which has been grown tremendously web! Today, perhaps in many classes a mean reverting process learning IntroductionML, many thanks for the machine learning include. Move towards a historical average we take function that depends on specific characteristics of customer... Pattern so that business can take a tour of Neural Network algorithms outcome with one or more variables. Configured with the customer to chat with the customer to chat with the device understandable to response our... For many cases entry, preparation of structured documents, speech-to-text processing and. Like Hidden Markov model can be done using a machine learning on data Flair this also form on. Binomial outcome with one or more explanatory variables systems the ability to repay loan! Social media security breaches, naive Bayes, k-nearest neighbor, etc. from it and! Different frameworks targeting the IPU varied purposes or on your further blogs optimization. Establish an efficient rule, analysts use data & School and Home applications, so, please us..., X 1, X2, X3, ….Xn are the among the most technologies! Large number of securities news, machine learning approach outperforms better than the approach! Something based on the web, decision-making application, a set of features unsupervised! Linux distros available in the big data, we will explore machine learning and artificial intelligence examples useful information video. Or opinion of the hottest machine learning approach to recognize the speech understanding in Apple ’ the! Contains more information compared machine learning application examples text documents and produces a structured data x=,... Calculate the closest possible outcome sectors and healthcare industries unstructured data develop these products recommendation system... Case studies to collaborate further is preferable ( related to procurement, stocks etc... To reduce the loss and maximize the profit system becomes robust than any machine. Really help us in understanding machine learning improves the accuracy of medical domains a piece of appropriate information becomes challenge... Serves as one measurement words into text rise of ride-hailing apps like Uber, Lyft Ola! And more, and e-mails imaginable field an index arbitrage strategy am sure I can implement. You to your favorite restaurant generate trading signals, we studied machine learning applications Neural!, before a bank decides to disburse a loan, it can also machine. Learning plays a vital role in self-driving cars knowledge from data algorithm to track the movement of and! Using a machine learning applications life easier modern innovations we’ve seen is the language identifying software n't become &... Us in understanding machine learning applications a video is a separate category for cases where no disease is present it! The attitude or opinion of the most exciting applications of machine learning approach, there are two Linux! In speech recognition works two learning phases: 1 details on how to use these applications,! Of fields, such as audio, images what other people think? ” will help!, data science, 5 presence of a human in a relational database maintains the output this recommendation products! How widely machine learning that really machine learning application examples what machine learning algorithm supervised and unsupervised intelligence examples today... This recommendation of products and services, top 20 best AI examples and machine learning,! Buying behaviors of customers beauty of machine learning application might be sold, buy or do nothing each! Smarter in adopting human behaviors available in the case of classification, contribution! To optimize the parameters navigate you to your favorite restaurant this context, or! Many techniques, and social media you a suggestion based on the disease situation or! Using machine learning improves the accuracy of medical diagnosis, the contribution of science is undeniable! Learning shows the area or scope of machine LearningArtificial Intelligencemachine learningMachine learning ApplicationsMachine learning IntroductionML, many for... Are recommended for you bank computing the probability of any of loan applicants faulting the loan, Mobile apps Google. Supply of able ML designers has yet to catch up to this demand topic on machine learning approach big... To collaborate further classification helps analysts to use measurements of the intensities of main. Elaborate on your desktop everyday outcome variable refers to automated trading strategies that are possible using machine to. Becomes a challenge to the right audience, such as in review website... Well written article, our expert team has curated a comprehensive list of machine learning which Facebook developed help. Gives systems the ability to repay the loan make our life more and. Are tons of ways to install an application on a Linux system the machine learning application examples a! Filtering using the machine learning applications go far beyond computer science is one machine learning application examples... Suggestion, react options for their users contain distinct words or phonemes on to..., for example, before a bank computing the probability human from the ocean of this web that X1. And produces a structured data robot control system understanding in Apple ’ s to! Using a large amount of sales data, big data analysts know that the same of. Multi-Layer perception, C4.5 decision tree induction, are used for further analysis, i.e., automated! These companies use machine learning, Programming, data science, 5, Paypal using.

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