Data Science World

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Sep
21
AI-Powered Text Response Analysis for Open-Ended Survey Questions

AI-Powered Text Response Analysis for Open-Ended Survey Questions

Introduction Open-ended questions are commonly used in surveys, particularly when the goal is to explore a subject in depth or
8 min read
Jan
20
Assessing Reliability: A Review of Failure Rates in Large-Scale IT System

Assessing Reliability: A Review of Failure Rates in Large-Scale IT System

1. Introduction As the complexity of large-scale IT infrastructures increases, with clusters encompassing millions of components, the challenge of managing
18 min read
Apr
23
Deep Learning Training Algorithm III: Second-Order Optimization Algorithms

Deep Learning Training Algorithm III: Second-Order Optimization Algorithms

In the previous blog post, we have introduced the Gradient-Based Optimization Algorithms, which use the first-order derivatives of the objective
6 min read
Apr
20
Deep Learning Training Algorithms II: Gradient-Based Optimization Algorithms

Deep Learning Training Algorithms II: Gradient-Based Optimization Algorithms

Introduction Deep learning models are powerful tools for solving complex problems in a variety of domains, from image and speech
10 min read
Apr
17
Deep Learning Training Algorithms I: Introduction

Deep Learning Training Algorithms I: Introduction

1. Introduction Deep learning has revolutionized the field of artificial intelligence, enabling machines to perform tasks that were previously thought
3 min read
Dec
11
Review of Deep Learning Algorithms and Architectures V: RNN and LSTM

Review of Deep Learning Algorithms and Architectures V: RNN and LSTM

1. Brief Introduction to Recurrent Neural Networks Recurrent neural networks or RNNs (Rumelhart et al., 1986) are a family of
6 min read
Dec
04
Review of Deep Learning Algorithms and Architectures IV: Boltzmann Machine

Review of Deep Learning Algorithms and Architectures IV: Boltzmann Machine

Boltzmann machines were originally introduced as a general "connectionist" approach to learning arbitrary probability distributions over binary vectors.
4 min read
Oct
23
Review of Deep Learning Algorithms and Architectures III: Autoencoder

Review of Deep Learning Algorithms and Architectures III: Autoencoder

Autoencoders are generalizations of PCA. A PCA transforms multi-dimensional data into a linear representation, whereas, autoencoders go further and produce
7 min read
Aug
21
Review of Deep Learning Algorithms and Architectures II: CNN Architectures

Review of Deep Learning Algorithms and Architectures II: CNN Architectures

A Deep neural network consists of several layers of nodes. Different architectures have been developed to solve problems in different
6 min read
Aug
08
Review of Deep Learning Algorithms and Architectures I: A Brief Introduction

Review of Deep Learning Algorithms and Architectures I: A Brief Introduction

Introduction Neural Network is a machine learning technique that is inspired by and resembles the human nervous system and the
7 min read