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
“It’s not the organizations that are competing. It’s the supply chains that are competing.” – Wael Safwat, SCMAO. The supply chain is essentially the backbone of any business: a living ecosystem that ensures the smooth, efficient, and consistent delivery of a product or service from a supplier to a customer. And if your supply chain is inefficient, ineffective, or fragmented, it could seriously hinder your commercial prospects.
ArticleVideos This article was published as a part of the Data Science Blogathon. Introduction Machine learning.Sounds cool right? When I see those two words, The post Introduction to Machine Learning for Absolute Beginners appeared first on Analytics Vidhya.
Here are some of the most significant themes we see as we look toward 2021. Some of these are emerging topics and others are developments on existing concepts, but all of them will inform our thinking in the coming year. MLOps FTW. MLOps attempts to bridge the gap between Machine Learning (ML) applications and the CI/CD pipelines that have become standard practice.
AI adoption is reshaping sales and marketing. But is it delivering real results? We surveyed 1,000+ GTM professionals to find out. The data is clear: AI users report 47% higher productivity and an average of 12 hours saved per week. But leaders say mainstream AI tools still fall short on accuracy and business impact. Download the full report today to see how AI is being used — and where go-to-market professionals think there are gaps and opportunities.
With the new year events well behind us, we’re steadily focused on moving forward in 2021. While we have seen a change in the calendar year, one initiative that continues to be a top priority for businesses is storing, managing, accessing and optimizing corporate data. Given that, let’s consider what I believe will be some […].
In January, our Dataiku Lab team presented their annual findings for up-and-coming machine learning (ML) trends , based on the work they do in machine learning research. In this series, we're going to break up their key topics (trustworthy ML, human-in-the-loop ML, causality, and the connection between reinforcement learning and AutoML) so they're easy for you to digest as you aim to optimize your ML projects in 2021.
ArticleVideos Introduction “I understand the concepts well. Why should I focus on data science projects in my data science journey?” I have been in. The post 6 Open Source Data Science Projects That Provide an Edge to Your Portfolio appeared first on Analytics Vidhya.
ArticleVideos Introduction “I understand the concepts well. Why should I focus on data science projects in my data science journey?” I have been in. The post 6 Open Source Data Science Projects That Provide an Edge to Your Portfolio appeared first on Analytics Vidhya.
Big data has shed some important insights on a number of facets of modern organizational functions. One of the areas that has been shaped by big data is cybersecurity. We have talked about the importance of using big data to strengthen cybersecurity by creating more robust defenses. However, there are also less direct reasons that big data can be important for stopping cyberattacks.
spaCy is a python library that provides capabilities to conduct advanced natural language processing analysis and build models that can underpin document analysis, chatbot capabilities, and all other forms of text analysis. The spaCy library is available under the MIT license and is developed primarily by Matthew Honnibal and Ines Montani from E xplosion.AI.
Our infographic explains how the open-source revolution has transformed data science and maps out how to become fluent in data manipulation, data visualization, machine learning, reporting and communicating data, and natural language processing.
ArticleVideos This article was published as a part of the Data Science Blogathon. What is Multicollinearity? One of the key assumptions for a regression-based. The post Multicollinearity: Problem, Detection and Solution 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
Data mining serves many essential purposes in numerous applications. It can be vital for identifying some of the most important social trends affecting people all over the country. Last April, we talked about ways that social data can be useful in business. However, social data can serve even more important purposes, especially for public policy makers, GMOs and leading nonprofits.
Metadata management is key to wringing all the value possible from data assets. However, most organizations don’t use all the data at their disposal to reach deeper conclusions about how to drive revenue, achieve regulatory compliance or accomplish other strategic objectives. What Is Metadata? Analyst firm Gartner defines metadata as “information that describes various facets of an information asset to improve its usability throughout its life cycle.
When choosing a data science use case, the ultimate goal is to leverage data to support a business decision or action. In simpler terms, just ask yourself: “What question am I trying to answer?” To respond, you will need to communicate and collaborate with your teams to determine any unsolved issues or ideas the company can benefit from — inclusivity is key to identifying all potential use cases or questions you will want to answer using data.
ArticleVideos This article was published as a part of the Data Science Blogathon. Photo by Max Fischer from Pexels Machine learning is used. The post A Simple Machine Learning Implementation to Predict Linear Algebra in Python appeared first on Analytics Vidhya.
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.
Big data is fundamental to the future of software development. A growing number of developers are finding ways to utilize data analytics to streamline technology rollouts. Data-driven solutions are particularly important for SaaS technology. New SaaS businesses have discovered that data analytics is important for facilitating many aspects of their models.
Part of the the series: Doing Power BI the Right Way Although my professional focus is building enterprise-scale BI solutions, I’ve created my share of informal Power BI reports that were put together quickly, with the goal to create something “good enough” rather then achieving perfection.
A recent survey by Kaggle revealed that data professionals used a variety of different ML algorithms in their work. On average, data professionals used two (median) algorithms. The most frequently used algorithms were 1) linear/logistic regression, 2) decision trees/random forests and 3) Convolutional Neural Networks. The total number of and use of specific algorithms varied across job titles, with ML engineers using the most (4) and DBA/Database Engineers using the least (1).
ArticleVideos This article was published as a part of the Data Science Blogathon. Pre-requisites Understanding of Machine Learning using Python (sklearn) Basics of Django. The post Machine Learning Model Deployment using Django appeared first on Analytics Vidhya.
GAP's AI-Driven QA Accelerators revolutionize software testing by automating repetitive tasks and enhancing test coverage. From generating test cases and Cypress code to AI-powered code reviews and detailed defect reports, our platform streamlines QA processes, saving time and resources. Accelerate API testing with Pytest-based cases and boost accuracy while reducing human error.
It is 2021 and many organizations still have too much data and too little ability to communicate it effectively. If you’re looking to add data storytelling skills to your organization, this is a list of world-class data storytelling thinkers and trainers. Why not learn from best? Lea Pica Lea Pica is one of my all-time favorite presenters and an energetic entrepreneur who honed her data storytelling skills with marketing data.
Banks regularly create campaigns to offer new products to their customers. According to market research, it’s easier to sell a product to an existing customer than to sell a product to a new, qualified prospect. In today’s marketplace, banks provide a variety of deposit, lending, and investment products to individuals and businesses, but a good proportion of current customers might only use one or two of them.
ArticleVideos This article was published as a part of the Data Science Blogathon. Introduction This article introduces the concept of Manifold Learning. It also. The post A Quick Introduction to Manifold Learning appeared first on Analytics Vidhya.
ZoomInfo customers aren’t just selling — they’re winning. Revenue teams using our Go-To-Market Intelligence platform grew pipeline by 32%, increased deal sizes by 40%, and booked 55% more meetings. Download this report to see what 11,000+ customers say about our Go-To-Market Intelligence platform and how it impacts their bottom line. The data speaks for itself!
In the newest release, Alation 2021.1, Alation takes big steps to further accelerate onboarding and adoption, expanding the catalog to welcome more classes of users, and lowering their barrier to entry with more organized information. In 2021.1, Alation increases search relevancy with data domains, adds new data governance capabilities, and speeds up time-to-insight with an Open Connector Framework SDK.
What is Project Management Report? A project management report is a high-level overview of the current status of a project. In another word, it is a formal and regular record of a project state at a given time. Why is project management report critical? To be more explicit about the importance of project management reports, let’s see what they can bring to companies: Monitor what’s working to encourage the explanation and focus Uncover what’s not working to facilitate reflectio
According to LinkedIn’s Emerging Jobs on the Rise report for 2021 , data scientist roles are still growing steadily, showing an average annual growth of 35%. As they occupy one of the most multifaceted (and in demand) roles in the data science, machine learning, and AI space, there are some clear skills that most data scientists possess — a general understanding of the industries and businesses they are working across (i.e., key challenges, top use cases), strong communication skills in order to
ArticleVideos This article was published as a part of the Data Science Blogathon. Introduction Medical Imaging plays an important role in modern medicine. It. The post A Gentle Introduction to AI for Medical Imaging appeared first on Analytics Vidhya.
Many software teams have migrated their testing and production workloads to the cloud, yet development environments often remain tied to outdated local setups, limiting efficiency and growth. This is where Coder comes in. In our 101 Coder webinar, you’ll explore how cloud-based development environments can unlock new levels of productivity. Discover how to transition from local setups to a secure, cloud-powered ecosystem with ease.
How do doctors feel about electronic health records (EHRs)? What do they want from this type of software? And what are the major barriers to doctors’ use of EHRs? should be your priority questions if you’ve decided to build custom healthcare software for your medical practice or implement an existing solution. Big data has had a tremendous affect on the healthcare sector.
Cloud-based contact center solutions are one of the most effective ways to scale up contact center capacity during the COVID-19 vaccine rollout. The approval of COVID-19 vaccines was cause for a lot of celebration—but it has also raised a lot of questions about the logistics of a nationwide vaccine rollout. Across the country, many organizations’ phone lines have been overwhelmed with questions from the public about vaccine eligibility, distribution and more.
Insurance is one of the many industries that has been tremendously shaken by the events of 2020. These unprecedented happenings are significantly reshaping the insurance market, pushing insurers to review their approach to numerous sectors and risks. This market shock should not overshadow the longer trends at play which are sustainably transforming the insurance business, across all business lines (P&C, life, savings, and commercial): longevity, health conditions, climate change, and the co
ArticleVideos This article was published as a part of the Data Science Blogathon. Introduction Coca-Cola and PepsiCo are well-established names in the soft drink. The post Customer Sentiments Analysis of Pepsi and Coca-Cola using Twitter Data in R appeared first on Analytics Vidhya.
Large enterprises face unique challenges in optimizing their Business Intelligence (BI) output due to the sheer scale and complexity of their operations. Unlike smaller organizations, where basic BI features and simple dashboards might suffice, enterprises must manage vast amounts of data from diverse sources. What are the top modern BI use cases for enterprise businesses to help you get a leg up on the competition?
We organize all of the trending information in your field so you don't have to. Join 42,000+ 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