This site uses cookies to improve your experience. To help us insure we adhere to various privacy regulations, please select your country/region of residence. If you do not select a country, we will assume you are from the United States. Select your Cookie Settings or view our Privacy Policy and Terms of Use.
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Used for the proper function of the website
Used for monitoring website traffic and interactions
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Strictly Necessary: Used for the proper function of the website
Performance/Analytics: Used for monitoring website traffic and interactions
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 […].
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.
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 […].
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.
Start building the AI workforce of the future with our comprehensive guide to creating an AI-first contact center. Learn how Conversational and Generative AI can transform traditional operations into scalable, efficient, and customer-centric experiences. What is AI-First? Transition from outdated, human-first strategies to an AI-driven approach that enhances customer engagement and operational efficiency.
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.
This article was published as a part of the Data Science Blogathon. Introduction FaceIO is a cross-browser framework for user facial recognition authentication. Any website can use a JavaScript snippet to implement it. As more and more daily tasks are managed electronically rather than with pen and paper or face-to-face, the demand for quick and […].
This article was published as a part of the Data Science Blogathon. Introduction FaceIO is a cross-browser framework for user facial recognition authentication. Any website can use a JavaScript snippet to implement it. As more and more daily tasks are managed electronically rather than with pen and paper or face-to-face, the demand for quick and […].
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 […].
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 […].
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 […].
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, […].
Today’s buyers expect more than generic outreach–they want relevant, personalized interactions that address their specific needs. For sales teams managing hundreds or thousands of prospects, however, delivering this level of personalization without automation is nearly impossible. The key is integrating AI in a way that enhances customer engagement rather than making it feel robotic.
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 […].
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.
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 […].
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.
Speaker: Ben Epstein, Stealth Founder & CTO | Tony Karrer, Founder & CTO, Aggregage
When tasked with building a fundamentally new product line with deeper insights than previously achievable for a high-value client, Ben Epstein and his team faced a significant challenge: how to harness LLMs to produce consistent, high-accuracy outputs at scale. In this new session, Ben will share how he and his team engineered a system (based on proven software engineering approaches) that employs reproducible test variations (via temperature 0 and fixed seeds), and enables non-LLM evaluation m
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 […].
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 […].
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 […].
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 […].
The DHS compliance audit clock is ticking on Zero Trust. Government agencies can no longer ignore or delay their Zero Trust initiatives. During this virtual panel discussion—featuring Kelly Fuller Gordon, Founder and CEO of RisX, Chris Wild, Zero Trust subject matter expert at Zermount, Inc., and Principal of Cybersecurity Practice at Eliassen Group, Trey Gannon—you’ll gain a detailed understanding of the Federal Zero Trust mandate, its requirements, milestones, and deadlines.
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.
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 […].
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.
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.
Speaker: Alexa Acosta, Director of Growth Marketing & B2B Marketing Leader
Marketing is evolving at breakneck speed—new tools, AI-driven automation, and changing buyer behaviors are rewriting the playbook. With so many trends competing for attention, how do you cut through the noise and focus on what truly moves the needle? In this webinar, industry expert Alexa Acosta will break down the most impactful marketing trends shaping the industry today and how to turn them into real, revenue-generating strategies.
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 […].
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 […].
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 […].
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.
Speaker: Joe Stephens, J.D., Attorney and Law Professor
Ready to cut through the AI hype and learn exactly how to use these tools in your legal work? Join this webinar to get practical guidance from attorney and AI legal expert, Joe Stephens, who understands what really matters for legal professionals! What You'll Learn: Evaluate AI Tools Like a Pro 🔍 Learn which tools are worth your time and how to spot potential security and ethics risks before they become problems.
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 […].
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. […].
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 […].
We organize all of the trending information in your field so you don't have to. Join 15,000+ users and stay up to date on the latest articles your peers are reading.
You know about us, now we want to get to know you!
Let's personalize your content
Let's get even more personalized
We recognize your account from another site in our network, please click 'Send Email' below to continue with verifying your account and setting a password.
Let's personalize your content