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Answer to : 50ml standard hard water (1.2gm CaCO3/L) requires 32ml of EDTA solution. 100ml of water sample consumes 14ml of EDTA solution. 100ml of boiled water takes 8.5ml of EDTA. Find temporary and non-carbonate hardness of water sample. is
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Definition The Fast Hadamard Transform (FHT) is an efficient algorithm used to compute the Hadamard Transform of a signal. The Hadamard Transform is a linear, orthogonal transform used in various applications such as signal processing, data compression, and error correction.…
Performance measures are essential in evaluating the quality and effectiveness of a machine learning model. Different performance measures are used depending on the type of problem being solved (classification, regression, clustering, etc.). Here are some common performance measures and how…
The Delta Learning Rule, also known as the LMS (Least Mean Squares) algorithm or the Widrow-Hoff rule, is a method for adjusting the weights of a linear neuron in a neural network during training. Below is a graphical representation of…
The Delta Learning Rule, also known as the LMS (Least Mean Squares) algorithm or the Widrow-Hoff rule, is a method for adjusting the weights of a linear neuron in a neural network during training. Below is a graphical representation of…
The perceptron model with bias is a fundamental building block of artificial neural networks, particularly in the realm of supervised learning for binary classification tasks. 1. Components of Perceptron with Bias: Input Features (𝑥1,𝑥2,…,𝑥𝑛): These are the features of the…
Overfitting and underfitting are two common problems that can occur when training machine learning models. Overfitting: Overfitting occurs when a model is too complex and learns the noise and random fluctuations in the training data, rather than the underlying patterns.…
Overfitting and underfitting are two common problems that can occur when training machine learning models. Overfitting: Overfitting occurs when a model is too complex and learns the noise and random fluctuations in the training data, rather than the underlying patterns.…
