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Showing posts with the label Machine Learning

Machine learning

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Machine learning Machine learning is a type of artificial intelligence that allows software applications to become more accurate in predicting outcomes without being explicitly programmed. This is achieved through the use of algorithms that iteratively learn from data, allowing the software to improve its performance on a specific task over time.

Don't be fooled by machine learning and deep learning

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Don't be fooled by machine learning and deep learning Deep learning and machine learning are the most popular words in the world of artificial intelligence. But do you know what deep learning and machine learning are? In fact, they are both parts of artificial intelligence. Although the parts of the same technology sound the same, they are completely different, but complementary to each other. Before understanding these two, let me explain what is artificial intelligence.

Facebook unveils new software that can translate into 100 languages

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Facebook unveils new software that can translate into 100 languages Facebook has unveiled a new software based on machine learning. Which can translate 100 languages ​​into English. Facebook claims it is the world's first software that can translate 100 languages ​​into English. Facebook's software is open-source artificial intelligence software. Content in more than 160 languages ​​on social media is designed to be translated into the user's language. More than two billion Facebook users will be able to take advantage of this software. Angela Fenn, the software's research assistant, said Facebook's research team had been working on the software for years. He claims that this new software is better than any other tool. "We want to translate from Chinese to French," Angela Fann said on her blog. But on most platforms, we have to translate from Chinese to English and from English to French. Because English training data is easily obtained. While our model ca

Artificial Intelligence and Machine Learning

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 The reference While presenting the Interim Budget for the year 2018-19, Union Minister Piyush Goyal also referred to Artificial Intelligence ie Artificial Intelligence. What is the government's plan for artificial intelligence? The government will open a National Center for Artificial Intelligence and soon the Artificial Intelligence Portal will also be launched. The new Artificial Intelligence Portal will be created in support of the National Program on Artificial Intelligence. The Artificial Intelligence program will be used to benefit people from Artificial Intelligence and its associated technology. Its national centers will be built which will act as hubs, currently, its 9 areas have been selected. The government has not given any information about what will happen in the proposed Artificial Intelligence Portal and how the people will be benefited from it. What is Artificial Intelligence? In 1955, John McCarthy first used the term Artificial Intelligence, which is why it is a

Unsupervised Machine Learning

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Unsupervised Machine Learning Unsupervised machine learning algorithms infer patterns from a dataset without reference to known or labeled, outcomes. Unlike supervised machine learning, unsupervised machine learning methods cannot be directly applied to regression or a classification problem because you have no idea what the values for the output data might be, making it impossible for you to train the algorithm the way you normally would. Unsupervised learning can instead be used to discover the underlying structure of the data. Why? It purports to uncover previously unknown patterns in data, but most of the time these patterns are poor approximations of what supervised machine learning can achieve. Additionally, since you do not know what the outcomes should be, there is no way to determine how accurate they are, making supervised machine learning more applicable to real-world problems. The best time to use unsupervised machine learning is when you do not have data on desired outcome

Prerequisite for Machine Learning

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Prerequisite for Machine Learning To get started with Machine Learning you must be familiar with the following concepts: Statistics Linear Algebra Calculus Probability Programming Languages Statistics Statistics contain tools that can be used to get some outcome from the data. There are descriptive statistics which is used to transform raw data into some important information. Also, inferential statistics can be used to get important information from a sample of data instead of using a complete dataset. To learn more about Statistics you can go through the following blogs: All You Need To Know About Statistics And Probability A Complete Guide To Maths And Statistics For Data Science Linear Algebra Linear algebra deals with vectors, matrices, and linear transformations. It is very important in machine learning as it can be used to transform and perform operations on the dataset. Calculus Calculus is an important field in mathematics and it plays an integral role in many machine learning

Artificial Intelligence (A.I.) and Machine Learning (M.L.)

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Artificial Intelligence (A.I.) and Machine Learning (M.L.) For the last few years, artificial intelligence has remained in equal discussion on various causes and issues. Artificial intelligence is a branch of computer science whose job is to make intelligent machines. Recently, the government think tank NITI Aayog and Google have agreed that both with the aim of promoting India's Artificial Intelliegence-AI and Machine Learning-ML ecosystem. They will work together on several initiatives, which will help to create an ecosystem of artificial intelligence in the country. NITI Aayog has been entrusted with the responsibility of developing technologies like AI and preparing national programs for research. On this responsibility, the NITI Aayog is developing a National Action Policy on Artificial Intelligence along with the National Data and Analytics Portal, so that it can be widely used. It may be noted that DeepMind, Google's artificial intelligence company, is working on several

The Real-World Benefits of Machine Learning in Healthcare

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The real-world benefits of machine learning in healthcare It is safe Medicine has many manual procedures. During the training, I hand wrote lab values, diagnoses, and other chart notes on paper. I always knew this was the place where technology could help improve my workflow and hopefully it also improves patient care. Since then, the progress of electronic medical records has been remarkable, but the information they provide is no better than replacing old paper charts. If technology is to improve care in the future, then the electronic information provided to doctors must be enhanced by the power of analytics and machine learning. Using these types of advanced analytics, we can provide better information to doctors on the point of patient care. With easy access to blood pressure and other important signals, I have seen my patients become regular and expectant. Imagine how much more useful it would be if I could read the last 500 blood pressure readings, laboratory test results, race,

Machine Learning in Astronomy

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Machine learning in astronomy Is astronomy data science? Machine learning in astronomy - Sure it sounds like an oxymoron, but is that the real case? Machine learning is one of the newest 'sciences', while astronomy is the oldest. In fact, astronomy developed naturally because people realized that studying the stars was not only fascinating, but it also helped them in their daily lives. For example, research into the star cycle helped create calendars (such as the Maya and the Proto-Bulgarian calendar). Also, it played an important role in navigation and orientation. Of particular importance was the early development of observational analysis using mathematical, geometric, and other scientific methods. It originated with the Babylonians, who laid the foundations for the tradition of astronomers, which will continue in many other civilizations. Since then, data analysis has played a central role in astronomy. So, after millennia of sophisticated techniques for data analysis, you