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Found 377 Articles for Artificial Intelligence
![Someswar Pal](https://www.tutorialspoint.com/assets/profiles/644125/profile/60_1440932-1682316355.jpg)
338 Views
Machine translation, voice recognition, and even the act of writing all benefit significantly from language modeling, which is an integral aspect of NLP. The well-known statistical technique "n-gram language modeling" predicts the nth word in a string given the previous n terms. This tutorial dives deep into using the Natural Language Toolkit (NLTK), a robust Python toolkit for natural language processing tasks, for N-gram language modeling. Understanding N-grams and Language Modeling As a first step in our study, we will examine the basics of N-grams and language models. N-grams are sequences of n elements occurring together in a text. ... Read More
![Someswar Pal](https://www.tutorialspoint.com/assets/profiles/644125/profile/60_1440932-1682316355.jpg)
78 Views
Machine learning systems often must deal with large amounts of data that must be processed quickly. Eigenvector computing and low-rank approximations are important ways to look at and work with data with many dimensions. In this article, we'll look at eigenvector processing and low-rank approximations, how they work, and how they can be used in machine learning. Eigenvector Computation Introduction to Eigenvectors and Eigenvalues Eigenvectors are unique vectors that give rise to scalar multiples of themselves when multiplied by a given matrix. Eigenvalues are the scale factors for the eigenvectors they are linked to. To understand how linear changes work, ... Read More
![Someswar Pal](https://www.tutorialspoint.com/assets/profiles/644125/profile/60_1440932-1682316355.jpg)
344 Views
Introduction In information retrieval and text analysis, solving problems is a vital part of finding the correct information from extensive collections of papers quickly and effectively. The Boolean and Vector Space Models are well-known models that offer different ways to solve problems. To improve knowledge retrieval processes, it is essential to understand these models and how they solve problems. Boolean Model The Boolean Model is a way to find information. It is based on Boolean logic about true and false numbers. This model shows documents and queries as sets of terms, where each term can be present (true) or missing ... Read More
![Someswar Pal](https://www.tutorialspoint.com/assets/profiles/644125/profile/60_1440932-1682316355.jpg)
123 Views
In sentiment analysis, "aspect modeling" means finding and analyzing specific parts or parts of a text that show views or feelings. Mood analysis is the polarity (positive, negative, or neutral) of people's feelings about something or someone in a text. Why is Aspect modeling crucial? Aspect modeling is important because it lets you look at ideas in a text more closely. Aspect modeling helps find the feelings that go along with the different parts or features of the text instead of just classifying the general mood of the text. It is beneficial for understanding customer feedback, product reviews, social media ... Read More
![Someswar Pal](https://www.tutorialspoint.com/assets/profiles/644125/profile/60_1440932-1682316355.jpg)
292 Views
Machine learning has revolutionized various industries by enabling computers to learn from data and make accurate predictions or decisions. One fundamental concept in machine learning is the projection perspective, which plays a crucial role in feature engineering, dimensionality reduction, and model optimization. In this article, we delve into the concept of projection perspective, its significance in machine learning, and its practical applications. By gaining a deeper understanding of the projection perspective, data scientists and machine learning practitioners can enhance their model performance and gain valuable insights from their data. Projection perspective is a machine learning technique used to reduce the ... Read More
![Someswar Pal](https://www.tutorialspoint.com/assets/profiles/644125/profile/60_1440932-1682316355.jpg)
80 Views
The No Free Lunch Theorem is a mathematical idea used in optimization, machine learning, and decision theory. It means that no one method can solve all optimization problems similarly. Practitioners must choose the right approach for each circumstance to get the greatest outcomes. This finding has significant consequences for overfitting and generalization in machine learning and the complexity of computing, optimization, and decision-making. Explanation of the No-free Lunch Theorem The NFL Theorem tells you about the theory and how hard the math is. It says that for each optimization problem, if a program solves one group of problems quickly, it ... Read More
![Someswar Pal](https://www.tutorialspoint.com/assets/profiles/644125/profile/60_1440932-1682316355.jpg)
418 Views
Introduction The introduction briefly overviews artificial neural networks and the Adaline architecture. It explains the concept of an OR gate, a fundamental logic gate used in digital circuit design. The goal is to train the Adaline network to output the correct OR gate truth table given different input combinations. Define the Input and Output Identify the input and output patterns for the OR gate. In the case of the OR gate, there are two input variables (x1 and x2) and one output variable (y). Generate Training Data Create a set of input-output training patterns that cover all possible combinations of ... Read More
![Someswar Pal](https://www.tutorialspoint.com/assets/profiles/644125/profile/60_1440932-1682316355.jpg)
416 Views
Controlling the crime rate and keeping people safe is essential for communities everywhere. Technological progress has made finding new ways to deal with these problems possible. One of these ways is to listen for and analyze people's screams, which could help with efforts to lower the crime rate. This piece discusses detecting and analyzing human screams, their importance in preventing crime, and the steps needed to make such a system. Understanding Human Scream Detection Audio analysis methods are used for human scream detection to find screams and tell them apart from other sounds. It is hard to do because screams ... Read More
![Hillol Modak](https://www.tutorialspoint.com/assets/profiles/661877/profile/60_2182474-1685597798.jpg)
147 Views
Introduction Machine learning calculations are significant in making sense of complex information designs and anticipating results. Weka, a well-known open-source instrument, gives a user-friendly interface to try with different machine learning methods. In this article, we'll investigate how to utilize classification machine learning calculations in Weka to build effective prescient models. We will walk through the steps, accompanied by significant code scraps, to guarantee a comprehensive understanding of the method. Importance of Classification Machine Learning Classification machine learning plays a vital part in different areas and applications, and its significance cannot be exaggerated. Here are a few key reasons why ... Read More
![Hillol Modak](https://www.tutorialspoint.com/assets/profiles/661877/profile/60_2182474-1685597798.jpg)
261 Views
Introduction on Naive Bayesian The Naive Bayesian classifier may be a primary, however viable probabilistic classifier based on Bayes' hypothesis. It expects that all highlights are autonomous of each other given the course variable, thus the term "naive." Despite this disentangling presumption, the classifier performs astoundingly well in numerous real-world applications. It calculates the likelihood of a given occasion having a place in each lesson and allocates the event to the class with the most elevated probability. The Gullible Bayesian classifier is especially valuable when managing expansive datasets and content classification errands, such as spam location or assumption investigation. WEKA ... Read More