Image Source: https://www.wipro.com/holmes/towards-future-farming-how-artificial-intelligence-is-transforming-the-agriculture-industry/

The term Artificial Intelligence can be described as the ability of machines to imitate cognitive functions including perception, learning, decision making, memory and language abilities, that are associated with human intelligence.

AI is steadily emerging and making a significant impact in various sectors such as education, healthcare, transportation, finance, manufacturing…


Access to quality healthcare and doctors has always been a concern in developing countries and remote areas. To deal with such issues, this healthcare web application is developed. Healthcare data was fed to machine learning training models and engines for predictive modelling. The accuracy of these models is directly proportional…


In Multiclass classification, the instances can be classified into one of three or more classes. Here, the Dataset contains image data of Natural Scenes around the world that are distributed into 6 different categories. {‘buildings’- 0, ‘forest’- 1, ‘glacier’- 2, ‘mountain’- 3, ‘sea’ - 4, ‘street’ - 5 }

There…


Loss function describes how efficient the model performs with respect to the expected outcome. Here, the main objective is to minimize the number of misclassifications. The choice of the loss function is critical in defining the outputs in a way that is sensitive to the application at hand. …


The activation function decides whether an artificial neuron should be activated or not. It helps the neural network learn complex patterns in the data and also helps to normalize the output of each neuron to a range between 1 and 0 or between -1 and 1. …


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Recurrent neural networks, also known as RNNs, are a class of neural networks that allow previous outputs to be used as inputs while having hidden states. RNN models are mostly used in the fields of natural language processing and speech recognition.

The vanishing and exploding gradient phenomena are often encountered…


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In this work, a binary classification model was designed that processes individual word with natural language processing methodologies to predict the presence of sarcasm in News Headlines.

NLP Terminologies

· Tokenization is essentially splitting a phrase, sentence, paragraph, or an entire text document into smaller units, such as individual words or terms…


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In this analysis, the presence of Epileptic Seizure is predicted by employing Support Vector Machine (SVM), Gaussian Naïve Bayes & Decision Tree (DT); Ensemble combination rules i.e., Majority Voting & Weighted Average Voting and Ensemble classifiers i.e., Bagging, Adaptive Boosting, Gradient Boosting XGBoost.

Parameters such as Accuracy, Precision, Recall and…


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Sentiment Analysis
Sentiment analysis is the contextual study that aims to determine the opinions, feelings, outlooks, moods and emotions of people towards entities and their aspects. …


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Long Short-Term Memory

Long Short Term Memory (LSTM) networks are a special kind of artificial recurrent neural network (RNN), capable of learning long-term dependencies. They were introduced by Hochreiter & Schmidhuber (1997) . LSTMs are explicitly designed to avoid the long-term dependency problem. Unlike standard feedforward neural networks, LSTM has feedback connections. It…

Harshita Pandey

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