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Author: Afzal Badshah, PhD

Demystifying Human Language for Machines: An Exploration of Natural Language Processing (NLP)

Demystifying Human Language for Machines: An Exploration of Natural Language Processing (NLP)

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Have you ever conversed with a virtual assistant on your phone or used a chat interface that seemed to grasp the meaning of your questions? Perhaps you’ve been amazed at the ability to translate languages in real-time during a video call. These remarkable feats are powered by a branch of Artificial Intelligence (AI) known as Natural Language Processing (NLP). NLP bridges the communication gap between humans and machines, enabling computers to understand, interpret, and even generate human language. This introductory…

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Broadcast Communication in MPI

Broadcast Communication in MPI

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In MPI (Message Passing Interface), broadcast communication is a fundamental operation that allows one process to efficiently send data to all other processes in a communicator. This means that a single piece of data is sent from one process, often referred to as the “root” process, to all other processes within the MPI environment. Broadcast communication is particularly useful for distributing global information or settings to all participating processes. How Broadcast Communication Works In MPI, broadcast communication works by having…

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Introduction to Scatter Operation in MPI

Introduction to Scatter Operation in MPI

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In MPI (Message Passing Interface) programming, the scatter operation is a collective communication pattern used to distribute data from one process to multiple processes. It takes an array or list of data on the root process and divides it into smaller chunks, then scatters these chunks to all other processes in the communicator. Each process receives one chunk of the data, allowing for parallel processing on different subsets of the data. Code: Explanation: Import the MPI module from the mpi4py…

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Cloud Computing Explained: Introduction, Technologies, Applications & Challenges

Cloud Computing Explained: Introduction, Technologies, Applications & Challenges

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We encounter cloud computing every day. For instance, if you use an Android phone, your photos and videos are likely backed up to a cloud service like Google Drive. Similarly, if you use Microsoft OneDrive, your data is copied to the cloud. Cloud computing also supports our email services, social media, and messaging apps like WhatsApp. But what exactly is cloud computing? Cloud computing can be defined as a utility service. Just like electricity, gas, or water, cloud computing provides…

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Introduction to Linear Regression: Exploring the Secrets of Prediction

Introduction to Linear Regression: Exploring the Secrets of Prediction

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Linear regression is a fundamental machine learning algorithm used for predicting a continuous outcome based on one or more input features. It assumes a linear relationship between the input features and the target variable, making it easy to interpret and implement. Visit the detailed tutorial here. Types of Linear Regression There are two main types of linear regression: Simple Linear Regression Simple linear regression models the relationship between one independent variable and the dependent variable using a linear equation. For…

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Monte Carlo Simulation: MPI4Py

Monte Carlo Simulation: MPI4Py

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Monte Carlo simulations are a statistical technique that allows for solving problems through random sampling. They are widely used in various fields such as physics, finance, and engineering to understand the impact of risk and uncertainty in prediction and forecasting models. The core idea is to use randomness to solve problems that might be deterministic in nature. You can visit the detailed tutorial here. For example, to estimate the value of Pi ((\pi)), we can use the Monte Carlo method….

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Introduction to Natural Language Processing (NLP)

Introduction to Natural Language Processing (NLP)

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Natural Language Processing (NLP) is a subfield of artificial intelligence (AI) that focuses on the interaction between computers and humans through natural language. The ultimate goal of NLP is to enable computers to understand, interpret, and generate human language in a way that is both meaningful and useful. Detailed tutorial on Data Science can be visited here. Key areas of NLP Text Analysis: Text analysis involves understanding and processing textual data to extract meaningful information. For example, in social media…

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Using Google Sheet API with Python

Using Google Sheet API with Python

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Here is the step-by-step guide to connecting Google Sheets to any Python program. In this tutorial, we connect it to Google Collab, but you can connect it to any application with the following the below points. Requirement: 1. Create a New Google Cloud Platform (GCP) Project 2. Enable Google Sheets API 3. Create a New Service Account 4. Download the JSON File Program side: Installed the required libraries Upload the JSON file, which you downloaded from the google API to…

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Ethics and Privacy in Data-Driven Applications

Ethics and Privacy in Data-Driven Applications

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The world is driven by Data. From our social media interactions to our fitness trackers, an ever-growing stream of information is generated every second. This vast ocean of data, known as big data, holds immense potential for innovation and progress. Businesses use it to personalize advertising, develop new products, and optimize operations. Researchers leverage it to understand diseases, track climate change, and make scientific discoveries. A detailed tutorial can be found here. However, the power of big data comes with…

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Parallel Programming Models: SIMD and MIMD

Parallel Programming Models: SIMD and MIMD

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With the ever-changing landscape of computing, the demand for faster and more efficient processing of big data has become necessary. Traditional sequential programming paradigms are often insufficient to meet these demands, demanding parallel programming techniques. Parallel programming programs the system to allow multiple tasks to be executed simultaneously, leveraging the capabilities of modern parallel hardware architectures. Visit the detailed tutorial on parallel and distributed computing here. Among these models, SIMD (Single Instruction, Multiple Data) and MIMD (Multiple Instruction, Multiple Data)…

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