2022

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Streamlit Tutorial: Building Web Apps with Code Examples

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Streamlit is an open-source tool to build and deploy data applications with less coding compared to other front-end technologies like HTML, CSS, and JavaScript. It is a low-code tool specifically designed for building data science applications. Moreover, the Streamlit library has functions […].

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Three R Libraries for Automated EDA

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction With the increasing use of technology, data accumulation is faster than ever due to connected smart devices. These devices continuously collect and transmit data that can be processed, transformed, and stored for later use. This collected data, known as big data, holds valuable […].

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Non-Generalization and Generalization of Machine learning Models

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction The generalization of machine learning models is the ability of a model to classify or forecast new data. When we train a model on a dataset, and the model is provided with new data absent from the trained set, it may perform […]. The post Non-Generalization and Generalization of Machine learning Models appeared first on Analytics Vidhya.

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An Introduction to Julia for Data Analysis

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Which language do we use when it comes to data analysis? Of course, Python, isn’t it? But there is one more language for data analysis which is growing rapidly. Some of you might guess the language – I am talking about Julia. […]. The post An Introduction to Julia for Data Analysis appeared first on Analytics Vidhya.

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The AI Productivity Shift: Whats Working & Whats Next

85% of teams are using AI, but only 27% report clear productivity gains. Why? Because most are still stuck in surface-level adoption. In this expert panel, top voices in workplace strategy and remote innovation—Dr. Gleb Tsipursky, Phil Kirschner, Nadia Harris, and Eryn Peters—reveal how leading teams are cutting digital noise, training AI to fit their workflows, and building cultures that embrace change.

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A Quick Guide to Blockchain: Merkle Tree

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction A Merkle tree is a basic component of blockchain technology. It is a mathematical data structure composed of hashes of different data blocks that serve as a summary of all transactions in the block. It also enables efficient and secure verification of […]. The post A Quick Guide to Blockchain: Merkle Tree appeared first on Analytics Vidhya.

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Famous Concurrency Problems in DBMS

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Concurrency in DBMS refers to the ability of the system to support multiple transactions concurrently without any data loss or corruption. In a concurrent system, numerous transactions can access and modify the data simultaneously. Each transaction is isolated from other transactions, so […].

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Data Science Tools for Vaccine Design and Development

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Biopharmaceutical Industries are the fastest growing industries after considering the basic need for the healthy life of humans and animals. Based on the available literature, the author has identified six major thrust areas of the Biopharmaceutical industry, which has summarized in the […].

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Underlying Engineering Behind Alexa’s Contextual ASR

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Conventionally, an automatic speech recognition (ASR) system leverages a single statistical language model to rectify ambiguities, regardless of context. However, we can improve the system’s accuracy by leveraging contextual information. Any type of contextual information, like device context, conversational context, and metadata, […].

Metadata 400
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How is Big Data Helping in the Development of Healthcare?

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction “Big data in healthcare” refers to much health data collected from many sources, including electronic health records (EHRs), medical imaging, genomic sequencing, wearables, payer records, medical devices, and pharmaceutical research. Its characteristics distinguish it from traditional electronic medical and human health data […].

Big Data 400
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Speeding Robotics Automation with AI

The $53 trillion manufacturing economy in the US is undergoing a major automation paradigm shift due to Artificial Intelligence (AI). Thanks to new practical frameworks, automation projects that were once impossible or inefficient to implement are now being fast-tracked, and robotics automation is becoming increasingly relevant to a growing number of users and scenarios.

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An Overview of Graph Machine Learning and Its Working

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Graph machine learning is quickly gaining attention for its enormous potential and ability to perform extremely well on non-traditional tasks. Active research is being done in this area (being touted by some as a new frontier of machine learning), and open-source libraries […].

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COVID-19 Diagnosis with Cough Audio Analysis

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Cough Audio analysis, one of the breakthroughs of AI in healthcare, often proves valuable in diagnosing respiratory and lung diseases. COVID-19 (Coronavirus Disease 2019) has had devastating effects on humanity, making early detection in patients imperative for its treatment.

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Building a simple Flask App using Docker vs Code

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction More often than not, developers run into issues of an application running on one machine versus not running on another. Dockers help prevent this by ensuring the application runs on any machine if it works on yours. Simply put, if your job as […]. The post Building a simple Flask App using Docker vs Code appeared first on Analytics Vidhya.

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Most Frequently Asked NLP Interview Questions

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Natural language processing (NLP) is the branch of computer science and, more specifically, the domain of artificial intelligence (AI) that focuses on providing computers the ability to understand written and spoken language in a way similar to that of humans. Combining computational linguistics […].

NLP 400
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Agentic AI Explained: Smarter Conversations, Better Experiences

AI has transformed how enterprises deliver customer service, enabling faster engagement, problem-solving, and cost savings. However, traditional AI Agents often rely on rigid conversation flows, risking customer trust when conversations stray from predefined paths. These limitations prevent businesses from fully realizing AI’s potential for cost-efficiency and productivity.

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Hierarchical Clustering in Machine Learning

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Hierarchical clustering is one of the most famous clustering techniques used in unsupervised machine learning. K-means and hierarchical clustering are the two most popular and effective clustering algorithms. The working mechanism they apply in the backend allows them to provide such a […].

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Introduction to Requests Library in Python

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Requests in Python is a module that can be used to send all kinds of HTTP requests. It is straightforward to use and is a human-friendly HTTP Library. Using the requests library; we do not need to manually add the query string […]. The post Introduction to Requests Library in Python appeared first on Analytics Vidhya.

Python 400
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Top Interview Questions on Voting Ensembles in Machine Learning

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Voting ensembles are the ensemble machine learning technique, one of the top-performing models among all machine learning algorithms. As voting ensembles are the most used ensemble techniques, there are lots of interview questions related to this topic that are asked in data […].

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How to Use DevOps Azure to Create CI and CD Pipelines?

Analytics Vidhya

This article was published as a part of the Data Science Blogathon Introduction In this article, we will discuss DevOps, two phases of DevOps, its advantages, and why we need DevOps along with CI and CD Pipelines. Before DevOps, software development teams, quality assurance (QA) teams, security, and operations would test the code for several […].

DevOps 398
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From Curiosity to Competitive Edge: How Mid-Market CEOs Are Using AI to Scale Smarter

Speaker: Lee Andrews, Founder at LJA New Media & Tony Karrer, Founder and CTO at Aggregage

This session will walk you through how one CEO used generative AI, workflow automation, and sales personalization to transform an entire security company—then built the Zero to Strategy framework that other mid-market leaders are now using to unlock 3.5x ROI. As a business executive, you’ll learn how to assess AI opportunities in your business, drive adoption across teams, and overcome internal resource constraints—without hiring a single data scientist.

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Frequently Asked Interview Questions on Naive Bayes Classifier

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction We, as data science and machine learning enthusiasts, have learned about various algorithms like Logistic Regression, Linear Regression, Decision Trees, Naive Bayes, etc. But at the same time, are we preparing for the interviews? As we know, the end goal is to […].

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Multi-variate Time Series Forecasting using Kats Model

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Kats model-which is also developed by Facebook Research Team-supports the functionality of multi-variate time-series forecasting in addition to univariate time-series forecasting. Often we need to forecast a time series where we have input variables in addition to ‘time’; this is where the […].

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Pandas Functions You Should Know for Data Analysis

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Any data science task starts with exploratory data analysis to learn more about the data, what is in the data and what is not. Having knowledge of different pandas functions certainly helps to complete the analysis in time. Therefore, I have listed […]. The post Pandas Functions You Should Know for Data Analysis appeared first on Analytics Vidhya.

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Using MongoDB with Pandas, NumPy, and PyArrow

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction If you are a data scientist or a Python developer who sometimes wears the data scientist hat, you were likely required to work with some of these tools & technologies: Pandas, NumPy, PyArrow, and MongoDB. If you are new to these terms, […]. The post Using MongoDB with Pandas, NumPy, and PyArrow appeared first on Analytics Vidhya.

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Prospect, Personalize, Profit: The New Way Sales & Marketing Teams Are Aligning with AI

Speaker: Kevin Burke, Founder & Managing Director at Digital One and AI & Automation Consultant

AI and automation are currently transforming the way sales and marketing teams operate. Generative AI crafts personalized outreach at scale, while conversational AI bots are engaging prospects in real time. Robotic process automation streamlines manual workflows by triggering tasks the moment a prospect takes a key action, and advanced AI analytics surface hidden patterns in the pipeline, improve forecasting, and help teams make data-driven decisions with confidence.

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Blockchain Technology and its Types

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Blockchain technology is a decentralized, distributed ledger that keeps a record of ownership of digital assets. Any data stored on the blockchain cannot be modified, making the technology a legitimate disruptor for payments, cybersecurity, and healthcare industries. Blockchain is a system of registering […].

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Top Interview Questions & Answers for Apache Sqoop

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction One of the sources of Big Data is the traditional application management system or the interaction of applications with relational databases using RDBMS. Such RDBMS-generated Big Data is kept in the relational database structure of Relational Database Servers. Big Data storage and analysis […].

Big Data 399
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Comprehensive Guide to Edge Detection Algorithms

Analytics Vidhya

Introduction Image processing is a widely used concept to exploit the information from the images. Image processing algorithms take a long time to process the data because of the large images and the amount of information available in it. So, in these edge-cutting techniques, it is necessary to reduce the amount of information that the […]. The post Comprehensive Guide to Edge Detection Algorithms appeared first on Analytics Vidhya.

Algorithm 399
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Minerva – Google’s Language Model for Quantitative Reasoning

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction to Minerva [link] Google presented Minerva; a neural network created in-house that can break calculation questions and take on other delicate areas like quantitative reasoning. The model for natural language processing is called Minerva. Recently, experimenters have developed a very sophisticated natural language […].

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Agent Tooling: Connecting AI to Your Tools, Systems & Data

Speaker: Alex Salazar, CEO & Co-Founder @ Arcade | Nate Barbettini, Founding Engineer @ Arcade | Tony Karrer, Founder & CTO @ Aggregage

There’s a lot of noise surrounding the ability of AI agents to connect to your tools, systems and data. But building an AI application into a reliable, secure workflow agent isn’t as simple as plugging in an API. As an engineering leader, it can be challenging to make sense of this evolving landscape, but agent tooling provides such high value that it’s critical we figure out how to move forward.

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An Introduction to MongoDB

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction When we hear the word “DATABASE”, the first thought that comes to our mind is SQL! No doubt, SQL and relational databases are widely popular and used extensively for storing data. Many kinds of literature, articles, and tutorials are on them internet-wide due to […].

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An Introductory Note on Principal Component Analysis

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction PCA, or Principal Component Analysis, is a term that is well-known to everyone. Notably employed for Curse of Dimensionality issues. In addition to this fundamental issue, there are other significant issues that we tackle in the PCA article. So, let’s start with […].

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Basic Concept Behind Apache Hive and Elasticsearch

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction I’ve always wondered how big companies like Google process their information or how companies like Netflix can perform searches in concise times. That’s why I want to tell you about my experience with two powerful tools they use: Apache Hive and Elasticsearch. […].