What is the difference between LSTM and GRU?

LSTM or Long Short Term Memory is a kind of Recurrent Neural Network that is capable of learning long-term patterns. It was developed by Schmidhuber and Hochreiter in 1997. It connects sequences of memory in a way that makes it difficult to remember each of the items for an extended period of time. A Globally…

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What is the difference between ANN and RNN?

ANN is a form of machine learning. It models the human brain and is a type of artificial neural network. ANNs are used to solve problems in the fields of computer vision, speech recognition, natural language processing, and other domains. .Artificial Intelligence is an umbrella term for a broad range of technologies that mimic the…

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What are Recommender Systems?

Recommender Systems are a type of AI that is used to predict what a user might like based on their interests, preferences, and historical data. The recommendation engine is personalized for the user, making suggestions that are not just based on similar tastes but also connections and social context. Recommendations include posts, products, or anything…

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Difference between R square and Adjusted R square?

Linear Regression, a machine learning algorithm, is widely used and evaluating its performance is essential. Two important metrics that are used to evaluate Linear Regression are R-squared and Adjusted R-squared. These metrics help determine the degree of the model fit and how much of the variance in the target variable is explained by the independent…

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Difference between Decision tree and Random Forest?

When it comes to the domain of machine learning algorithms, two prevalent models are the decision trees and the random forests. While both are employed for classification and regression, they diverge in their data analysis and model building methodologies. Decision Trees A decision tree is a model that segments the presented data into minor subsets…

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Difference between Artificial Intelligence, Machine Learning and Deep Learning?

Artificial intelligence (AI) is a term that encompasses computer systems designed to imitate human intelligence. It is an exciting field that has attracted considerable attention in many industries, including finance, hospitality, education and entertainment. Artificial intelligence is planned to simulate human behavior and thought processes, making it one of the most important trends of this…

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What is bag of words?

We are going to talk about a Natural Language Processing concept called the Bag of words model. When you’re applying an algorithm in NLP, it works with numbers and not words or sentences. We can’t feed our text directly into algorithms like that in order to analyze text data, it needs to be converted into…

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What is CatBoost and How Does it Improve Machine Learning?

CatBoost is a powerful machine learning library that was developed by researchers at the University of Montreal, McGill University, and Google Brain. It was designed to speed up the training of deep neural networks and improve the accuracy of predictions in machine learning models. Using CatBoost for Text Classification One of the key benefits of…

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LightGBM: A High-Performance Gradient Boosting Framework for Machine Learning

LightGBM, an open-source gradient boosting framework, provides swift and accurate solutions for various machine learning applications. Developed by Microsoft Research, LightGBM aims to deliver highly efficient training processes, making it a top choice among large corporations. Parallelized Tree Architecture: The Inner Workings of LightGBM LightGBM’s core lies in its parallelized tree architecture, which allows for…

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XGBoost: The Decision Tree-Based Ensemble Machine Learning Algorithm

XGBoost is a data science algorithm that has revolutionized predictive modeling. Created in 2013 by Tianqi Chen and Guodong Ji, this machine learning algorithm has become popular due to its remarkable predictive capabilities. In this composition, we will delve into the intricacies of XGBoost, its essential attributes, and why it is a perfect option for…

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