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Category Archives: Machine Learning

Prerequisite: Regression and Classification | Supervised Machine Learning Sensors which are placed in road junctions collect the data of no of vehicles at different junctions… Read More
Neural networks consist of simple input/output units called neurons (inspired by neurons of the human brain). These input/output units are interconnected and each connection has… Read More
In this article, we’ll learn about the StratifiedShuffleSplit cross validator from sklearn library which gives train-test indices to split the data into train-test sets.  What… Read More
In this article, we are going to learn how we can automate sending emails using Uipath Studio. This project is a basic application of Robotic… Read More
Let us see how to predict the air quality index using Python. AQI is calculated based on chemical pollutant quantity. By using machine learning, we… Read More
COVID-19 pandemic is one of the biggest challenges for the healthcare system right now. It is a respiratory disease that affects our lungs and can… Read More
Prerequisites: LTSM, GRU In this article, we will be discussing a deep learning toolkit used to improve the training time of the current Speech Recognition… Read More
Text preprocessing is a crucial step in NLP. Cleaning our text data in order to convert it into a presentable form that is analyzable and… Read More
Prerequisite: BERT Model SpanBERT vs BERT SpanBERT is an improvement on the BERT model providing improved prediction of spans of text. Unlike BERT, we perform… Read More
Open AI GPT-3 is proposed by the researchers at OpenAI as a next model series of GPT models in the paper titled “Language Models are… Read More
Introduction: Logistic Regression is a supervised learning algorithm that is used when the target variable is categorical. Hypothetical function h(x) of linear regression predicts unbounded… Read More
The max_error() function computes the maximum residual error. A metric that captures the worst-case error between the predicted value and the true value. This function… Read More
Radius Neighbors is also one of the techniques based on instance-based learning. Models based on instance-based learning generalize beyond the training examples. To do so,… Read More
Prerequisites :  Optimization techniques in Gradient Descent Adam Optimizer  Adaptive Moment Estimation is an algorithm for optimization technique for gradient descent. The method is really… Read More
NLP Sequencing is the sequence of numbers that we will generate from a large corpus or body of statements by training a neural network. We… Read More