## Ridge and Lasso Regression Explained

Premansh Sharma

Updated on 13-Apr-2023 17:35:16

Introduction Two well-liked regularization methods for linear regression models are ridge and lasso regression. They help to solve the overfitting issue, which arises when a model is overly complicated and fits the training data too well, leading to worse performance on fresh data. Ridge regression reduces the size of the ... Read More

## Naive Bayes algorithm: Prior, likelihood and marginal likelihood

Premansh Sharma

Updated on 13-Apr-2023 17:26:01

Introduction Based on Bayes' theorem, the naive Bayes algorithm is a probabilistic classification technique. It is predicated on the idea that a feature's presence in a class is unrelated to the presence of other features. Applications for this technique include text categorization, sentiment analysis, spam filtering, and picture recognition, among ... Read More

## What is learning rate in Neural Networks?

Premansh Sharma

Updated on 13-Apr-2023 17:24:43

In neural network models, the learning rate is a crucial hyperparameter that regulates the magnitude of weight updates applied during training. It is crucial in influencing the rate of convergence and the caliber of a model's answer. To make sure the model is learning properly without overshooting or converging too ... Read More

## Fixing constant validation accuracy in CNN model training

Premansh Sharma

Updated on 13-Apr-2023 17:23:44

Introduction The categorization of images and the identification of objects are two computer vision tasks that frequently employ convolutional neural networks (CNNs). Yet, it can be difficult to train a CNN model, particularly if the validation accuracy approaches a plateau and stays that way for a long time. Several factors, ... Read More

## Activation Function in a Neural Network: Sigmoid vs Tanh

Premansh Sharma

Updated on 13-Apr-2023 17:22:51

Introduction Due to the non-linearity that can introduce towards the output of neurons, activation functions are essential to the functioning of neural networks. Sigmoid and tanh are two of the most often employed activation functions in neural networks. Binary classification issues frequently employ the sigmoid function in the output layer ... Read More

## CNN vs ANN for Image Classification

Premansh Sharma

Updated on 13-Apr-2023 17:21:33

Introduction There has been a lot of interest in creating efficient machine-learning models for picture categorization due to its growing significance in several industries, including security, autonomous driving, and healthcare. Artificial neural networks (ANNs) and convolutional neural networks (CNNs) are two common models for classifying images. While both CNNs and ... Read More

## What is momentum in Machine Learning?

Premansh Sharma

Updated on 13-Apr-2023 17:20:05

Optimization algorithms are frequently used in machine learning models to identify the best collection of parameters that minimize a particular cost function. Momentum is a common optimization technique that is frequently utilized in machine learning. Momentum is a strategy for accelerating the convergence of the optimization process by including a ... Read More

## Role of weight transmission Protocol in Machine Learning

Premansh Sharma

Updated on 13-Apr-2023 17:19:01

Introduction Federated machine learning allows machine learning models to be trained across various dispersed devices without requiring data to be sent to a central server. The weight transmission protocol is a critical component of federated machine learning since it is in charge of communicating model weights between client devices and ... Read More

## How to resume Python Machine Learning if the Machine has restarted?

Premansh Sharma

Updated on 13-Apr-2023 17:18:18

Introduction Python ranks as one of the most widely used programming languages for machine learning for its simplicity of being used, adaptability, and broad library and tool set. Yet, one challenge that many developers have when working with Python for machine learning is how to resume work if their system ... Read More

## Best practices to handle errors in node-red

Premansh Sharma

Updated on 13-Apr-2023 17:17:33

Introduction Node-RED is a well-liked and effective tool for building intricate workflows and automating processes. Yet, given the number of nodes and connections, faults frequently happen and might potentially stop the flow of data. The usage of error handling nodes, how to detect and resolve faults, and how to adopt ... Read More