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What Is Training Data? How It's Used in Machine Learning

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Training data is the initial dataset used to train machine learning algorithms. Models create and refine their rules using this data. It's a set of data samples used to fit the parameters of a machine learning model to training it by example.


Machine-learning improves the prediction of stroke recovery

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When blood flow to the brain is somehow reduced or restricted, a person can suffer a stroke. Stroke is fairly common; in Europe alone, there are over 1.5 million new cases each year. Some strokes can be lethal, and when they're not, they often result in serious damage to the victim's ability to move. In fact, stroke is one of the major causes of long-term disability today. Recovery can be a long and arduous road.


iiot ai_2021-07-30_03-17-11.xlsx

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The graph represents a network of 1,283 Twitter users whose tweets in the requested range contained "iiot ai", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Friday, 30 July 2021 at 10:25 UTC. The requested start date was Friday, 30 July 2021 at 00:01 UTC and the maximum number of tweets (going backward in time) was 7,500. The tweets in the network were tweeted over the 2-day, 10-hour, 29-minute period from Tuesday, 27 July 2021 at 13:30 UTC to Friday, 30 July 2021 at 00:00 UTC. Additional tweets that were mentioned in this data set were also collected from prior time periods.


Minute Article - Member Blogs - By Madhavi Desai

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Using the blend of technologies similar to Artificial Intelligence like Machine Learning, Deep Learning, Natural Language Processing, Neural Networks, etc, These decision support systems outshines its ability to analyze patterns, simplify processes by examining large amounts of volumetric data, and spot business opportunities. With the help of computerized models using self-learning technologies like data mining, pattern recognition, and natural language processing, Cognitive computing synthesizes the data fed to machine learning algorithms from different information sources to suggest the best possible answers. Pitching on the grounds of learning, reasoning, and self-correction and assisting humans to make smarter decisions, Cognitive Computing applications include speech recognition, sentiment analysis, face detection, risk assessment, and fraud detection.


Artificial Intelligence pioneered at Oxford to detect floods launches into space

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The work is a first step towards relaying real time information from space to disaster response teams. The Oxford team has developed a machine learning / artificial intelligence model called'Worldfloods' designed specifically for deployment in specialized hardware in space on low-cost satellites in Low Earth Orbit. The model is a flood segmentation model that has the purpose of detecting flood events and significantly improving disaster response operations. It has major implications in bringing down the cost of such technologies and making it accessible for low income countries. Atilim Güneş Baydin, based at the Departments of Engineering Science and Computer Science, Oxford, said: 'This will be the first time a machine learning model for this type of task will be actually deployed in space.


Deep Learning Approach to Detect Banana Plant Diseases

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Hello folks:) This is my final year research project based on deep learning. Let me give an introduction about my project first. When we talk about banana it's a famous fruit that commonly available across the world, because it instantly boosts your energy. Bananas are one most consumed fruit in the world. According to modern calculations, Bananas are grown in around 107 countries since it makes a difference to lower blood pressure and to reduce the chance of cancer and asthma.


Machine Learning Model Interpretation - KDnuggets

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Interpreting a machine learning model is a difficult task because we need to understand how a model works in the backend, what all parameters the model uses, and how the model is generating the prediction. There are different python libraries that we can use to create machine learning model visualizations and analyze who the model is working. Staker is an open-source python library that enables machine learning model interpretations for different types of black-box models. It helps us create different types of visualization, making it easier to understand how a model is working. In this article, we will explore Skater and what are its different functionalities.


5 Best Free Artificial Intelligence and Deep Learning Courses for Beginners in 2021 - Best of Lot

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Hello guys, if you are interested in learning about Artificial Intelligence and how to build AI and looking for free online resources then you have come to the right place. Earlier, I have shared free Machine Learning and Free Data Science courses and in this article, I am going to share free Artificial Intelligence and deep learning courses for beginners. These free courses are created from Udemy, Coursera, edX, and Pluralsight and created by experts and trusted by thousands of people who wanted to learn Artificial Intelligence. Clicking on this article link shows that you are very interested to understand and learn more about artificial intelligence but wait! Learning artificial intelligence is not that easy and never will be.


Microsoft FLAML VS Traditional ML Algorithms: A Practical Comparison

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Machine learning has been an important component in the vastly growing field of data science. Making use of statistical methods, different algorithms are used to create models, which are further trained to make classifiers or prediction systems, which help uncover key insights within data mining and exploration projects. These insights later drive the decision-making process within created applications and businesses, deeply impacting its growth metrics in particular. As big data continues to expand and grow in today's world, the demand for data scientists has increased, requiring them to identify relevant business questions and subsequently use data and exploration tools and techniques to answer them. This can be done using methods of Machine and Deep Learning.


Types of Learning in AI

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Artificial intelligence, Machine learning and Neural Network are few buzzwords in today's world. Every body knows about it or want to know about it. This will be the trend of things going to be in next decade which will rule the technology. We can understood from this only that machine learning products capable of predicting like human. They are not absolutely correct but probabilistically best in the given condition.