Overfitting and Underfitting in Machine Learning

In machine learning, overfitting and underfitting are two common problems that can occur when training a model. They are related to the model’s ability to generalize its predictions to unseen data. Here’s an explanation of each term: Signs of overfitting include: To mitigate overfitting, you can try the following: Signs of underfitting include: To address underfitting,…

Computational Learning theory (CLT)

Definition and Purpose: Computational learning theory is a branch of theoretical computer science that focuses on mathematically analyzing learning algorithms. Its goal is to understand the principles and limitations of machine learning, providing a theoretical foundation for studying the efficiency, accuracy, and generalization properties of learning algorithms. Key Concepts in Computational Learning Theory 1. Learning…

Long Short-Term Memory (LSTM) in Deep Learning

Long Short-Term Memory (LSTM) is a type of recurrent neural network (RNN) architecture that addresses the vanishing gradient problem and enables the modeling of long-term dependencies in sequential data. LSTMs have several benefits and a unique working mechanism that sets them apart from traditional RNNs. Here’s an overview: Benefits of LSTMs: Working of LSTMs: Long…

IntelliCode

IntelliCode is a tool in Microsoft’s Visual Studio and Visual Studio Code. It uses machine learning to suggest better code completions based on the code’s context. The working of IntelliCode involves analyzing patterns in code to predict what code a developer is likely to write next. The models learn how programmers write by using big…

What is Speech Recognition?

Speech recognition is the technology that allows machines to understand and interpret human speech. Algorithms and machine learning can transform spoken words into text or commands. Computers and other devices can understand and act on them. let we explain how it works and what its benefits are: This technology works by analyzing the acoustic patterns…

Gradient descent optimization algorithms

Gradient descent optimization algorithms is a widely used optimization algorithms in machine learning to minimize the cost function of a model. The cost function measures the difference between the predicted output and the actual output. Also, the objective is to find the set of parameters that minimize the cost function. Gradient descent works by computing…

Banking Bot and its uses

A Banking Bot is a computer program or an AI-powered chatbot. Banking Bot is designed to provide banking services and assistance to customers through digital channels. It uses NLP and ML algorithms to understand and respond to customer queries in real time. Banking bots can perform a variety of functions. For example, checking account balances,…