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
Over the past decade, CIOs have invested significantly in digital transformation initiatives in an effort to improve customer experiences, build data analytics capabilities, and deliver productivity enhancements with automation. Underpinning these initiatives is a slew of technology capabilities and strategies aimed at accelerating delivery cycles, such as establishing product management disciplines, building cloud architectures, developing devops capabilities, and fostering agile cultures.
Introduction Programmers often prefer Python due to its easy-to-read syntax and friendliness towards beginners. However, hiding underneath is a strong word collection that controls how your code works: keywords. These specific words are important in the Python interpreter, serving as the foundational elements for developing strong programs. As bricks build a house, keywords are the […] The post All of the Python Keywords You Need to Know appeared first on Analytics Vidhya.
Introduction Unlocking the potential for intuitive and expressive code, operator overloading in Python stands as a cornerstone of flexibility and customizability. It empowers developers to infuse their classes with operator semantics, bridging the gap between abstract concepts and concrete implementations. By reimagining operators such as +, -, *, or and within custom classes, Python transcends […] The post Python Membership and Identity Operators: Understanding the Basics appeared first o
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
Introduction Unlocking the potential for intuitive and expressive code, operator overloading in Python stands as a cornerstone of flexibility and customizability. It empowers developers to infuse their classes with operator semantics, bridging the gap between abstract concepts and concrete implementations. By reimagining operators such as +, -, *, or within custom classes, Python transcends conventional […] The post Here’s All About the Operator Overloading in Python appeared first o
Introduction A reliable statistical technique for determining significance is the analysis of variance (ANOVA), especially when comparing more than two sample averages. Although the t-distribution is adequate for comparing the means of two samples, an ANOVA is required when working with three or more samples at once in order to determine whether or not their […] The post One-Way and Two-Way Analysis of Variance (ANOVA) appeared first on Analytics Vidhya.
Data science’s essence lies in machine learning algorithms. Here are ten algorithms that are a great introduction to machine learning for any beginner!
Introduction Artificial Intelligence has many use cases, and some of the best ones are in the Health Industry. It can really help people maintain a healthier life. With the increasing boom in generative AI, certain applications are made these days with less complexity. One very useful application that can be built is the Calorie Advisor […] The post How to Build a Calorie Advisor App Using GenAI?
In March 2024, we announced the general availability of the generative artificial intelligence (AI) generated data descriptions in Amazon DataZone. In this post, we share what we heard from our customers that led us to add the AI-generated data descriptions and discuss specific customer use cases addressed by this capability. We also detail how the feature works and what criteria was applied for the model and prompt selection while building on Amazon Bedrock.
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.
OpenAI’s latest advancement, Voice Engine, is reshaping the landscape of voice cloning technology. This new AI tool holds immense potential as it can replicate a person’s voice from a mere 15-second audio sample. However, such generative AI technology comes with concerns of misuse and ethical considerations. Hence, OpenAI has opted for a cautious approach, limiting […] The post OpenAI Develops New Voice Cloning AI; Halts Release Due to Risk of Misuse appeared first on Analytics
You can use Amazon Data Firehose to aggregate and deliver log events from your applications and services captured in Amazon CloudWatch Logs to your Amazon Simple Storage Service (Amazon S3) bucket and Splunk destinations, for use cases such as data analytics, security analysis, application troubleshooting etc. By default, CloudWatch Logs are delivered as gzip-compressed objects.
It’s been said that the Federal Government is one of, if not the largest, producer of data in the United States, and this data is at the heart of mission delivery for agencies across the civilian to DoD spectrum. Data is critical to driving the innovation and decision-making that improves services, streamlines operations and strengthens national security.
In today’s fast-paced digital economy, businesses are fighting to stay ahead and devise new ways to streamline operations, enhance responsiveness and work with real-time insights. We are now in an era defined by being proactive, rather than reactive. In order to stay ahead, businesses need to enable proactive decision making—and this stems from building an IT infrastructure that provides the foundation for the availability of real-time data.
Savvy B2B marketers know that a great account-based marketing (ABM) strategy leads to higher ROI and sustainable growth. In this guide, we’ll cover: What makes for a successful ABM strategy? What are the key elements and capabilities of ABM that can make a real difference? How is AI changing workflows and driving functionality? This Martech Intelligence Report on Enterprise Account-Based Marketing examines the state of ABM in 2024 and what to consider when implementing ABM software.
More than 600 companies worldwide use Dataiku, bringing together experts from across their organizations for faster time to value on data and AI projects. But how much faster is faster? And what other cost savings and benefits does Dataiku drive? Forrester: The Total Economic Impact™ Of Dataiku has quantified answers.
The US and the UK have signed an agreement to test the safety of large language models (LLMs) that underpin AI systems. The agreement or memorandum of understanding (MoU) — signed in Washington by US Commerce Secretary Gina Raimondo and UK Technology Secretary Michelle Donelan on Monday — will see both countries working to align their scientific approaches and working closely to develop suites of evaluations for AI models, systems, and agents.
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