Introduction and Motivation

Introduction and Motivation

It is becoming increasingly common for organizations to collect very large amounts of data over time, and to…

Predict Number of Active Cases by Covid-19 Pandemic based on Medical Facilities (Volume of Testing, ICU beds, Ventilators, Isolation Units, etc) using Multi-variate…

                                           Source…

Importance of C++ in Data Science and Big Data

Introduction and Motivation – Why C++

C++ is ideal for dynamic load balancing, adaptive…

Introduction and Motivation

With the effect of the pandemic increasing every day and casting a vehemently toxic influence in almost all parts of the world, it becomes important how can we contain the…

Comparative Study of Different Adversarial Text to Image Methods

Introduction

Automatic synthesis…

Scaling AI with Dynamic Inference Paths in Neural Networks

Introduction

IBM Research, with the help of the University of Texas Austin and the University of Maryland, has tried to expedite the performance of neural networks by creating technology, called BlockDrop. Behind the design of this technology lies the objective and promise of speeding up convolutional neural network operations without…

Use of SecureSVM, Boosting, Bagging, Clustering, LSTM, CNN, GAN in Retail with BlockChain

Introduction

This blog highlights different ML algorithms used in blockchain transactions with a special emphasis on bitcoins in retail payments. This blog is structured as follows:

• Overview of the role of blockchain in the retail industry.
• Different traditional…

Anomaly Detection from Head and Abdominal Fetal ECG — A Case study of IOT anomaly detection using Generative Adversarial Networks

Unsupervised Anomaly Detection via Variational Auto-Encoder for Seasonal…

Motivation

There are five types of traditional time series models most commonly used in epidemic time series forecasting, which includes

• Autoregressive (AR),
• Moving Average (MA),
• Autoregressive Moving Average (ARMA),
• Autoregressive Integrated Moving Average (ARIMA), and
• Seasonal Autoregressive Integrated Moving Average (SARIMA) models.

AR models express the current value of the time series linearly in…

Traditional vs Deep Learning Algorithms in the Telecom Industry — Cloud Architecture and Algorithm Categorization

Google Cloud Architecture for Machine Learning Algorithms in the Telecom Industry

Introduction

The unprecedented growth of mobile devices, applications, and services have placed the utmost demand on mobile and wireless networking infrastructure. Rapid research…