Sat.Oct 28, 2023 - Fri.Nov 03, 2023

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Generative AI vs Machine Learning: Which One to Choose?

Knowledge Hut

Artificial Intelligence has transformed the way we tackle intricate problems, interpret data, and make forecasts, revolutionizing the tech realm with its uninhabited prowess and potential. In fact, did you know that the global market for AI , which currently stands at a market value of $150.2 billion, is expected to witness a 36.8% CAGR by the end of 2030?

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Azure Data Engineer vs Azure DevOps: Top 8 Differences

Knowledge Hut

For those aspiring to build a career within the Azure ecosystem, navigating the choices between Azure Data Engineers and Azure DevOps Engineers can be quite challenging. Azure Data Engineers and Azure DevOps Engineers are two critical components of the Azure ecosystem for different but interconnected reasons. A choice between these two can be difficult to make unless you have all the information you need.

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Handling a Regional Outage: Comparing the Response From AWS, Azure and GCP

The Pragmatic Engineer

👋 Hi, this is Gergely with a bonus, free issue of the Pragmatic Engineer Newsletter. In every issue, I cover topics related to Big Tech and startups through the lens of engineering managers and senior engineers. In this article, we cover three out of seven topics from today’s subscriber-only issue Three Cloud Providers, Three Outages: Three Different Responses.

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What's new in Apache Spark 3.5.0 - watermark propagation

Waitingforcode

Watermark, or rather multiple watermarks management, has been a thorn in the side of Apache Spark Structured Streaming. It has improved in the previous release (3.4.0) but still had some room for improvement. Well, it did have because the 3.5.0 release brought a serious fix for the multiple watermarks scenario.

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Navigating the Future: Generative AI, Application Analytics, and Data

Generative AI is upending the way product developers & end-users alike are interacting with data. Despite the potential of AI, many are left with questions about the future of product development: How will AI impact my business and contribute to its success? What can product managers and developers expect in the future with the widespread adoption of AI?

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7 Machine Learning Algorithms You Can’t Miss

KDnuggets

This list of machine learning algorithms is a good place to start your journey as a data scientist. You should be able to identify the most common models and use them in the right applications.

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Training LLMs at Scale with AMD MI250 GPUs

databricks

Introduction Four months ago, we shared how AMD had emerged as a capable platform for generative AI and demonstrated how to easily and.

More Trending

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Top 30+ Computer Science Project Topics of 2023 [Source Code]

Knowledge Hut

Choosing the best computer science project topic is critical to the success of any computer science student or employee. After all, the more engaging and interesting topic, the more likely it is that students or employees will be able to stay motivated and focused throughout the duration of the project. However, with so many options out there, it can be tough to decide which one is right for you.

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Hyperparameter Tuning: GridSearchCV and RandomizedSearchCV, Explained

KDnuggets

Learn how to tune your model’s hyperparameters using grid search and randomized search. Also learn to implement them in scikit-learn using GridSearchCV and RandomizedSearchCV.

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Announcing MLflow 2.8 LLM-as-a-judge metrics and Best Practices for LLM Evaluation of RAG Applications, Part 2

databricks

Today we're excited to announce MLflow 2.8 supports our LLM-as-a-judge metrics which can help save time and costs while providing an approximation of.

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Harness the Power of Pinecone with Cloudera’s New Applied Machine Learning Prototype

Cloudera

Elevate your AI applications with our latest applied ML prototype At Cloudera, we continuously strive to empower organizations to unlock the full potential of their data, catalyzing innovation and driving actionable insights. And so we are thrilled to introduce our latest applied ML prototype (AMP) — a large language model (LLM) chatbot customized with website data using Meta’s Llama2 LLM and Pinecone’s vector database.

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Get Better Network Graphs & Save Analysts Time

Many organizations today are unlocking the power of their data by using graph databases to feed downstream analytics, enahance visualizations, and more. Yet, when different graph nodes represent the same entity, graphs get messy. Watch this essential video with Senzing CEO Jeff Jonas on how adding entity resolution to a graph database condenses network graphs to improve analytics and save your analysts time.

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AI prompt engineering benefits

InData Labs

AI prompt engineering has taken center stage in many professional circles as of late. This is because businesses have been able to garner better results with AI using prompt engineering techniques. With the right prompt engineering strategy, the results of all AI and ML applications are improved. Many individuals have also switched careers due to. Запись AI prompt engineering benefits впервые появилась InData Labs.

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AI vs Data Analysts: Top 6 Limitations Impacting the Future of Analytics

KDnuggets

AI have ability to reason, and generate functioning code in languages like Python, SQL, and R, they can provide impressive value with Data analysis. But can they replace data analysts?

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Big Book of MLOps Updated for Generative AI

databricks

Last year, we published the Big Book of MLOps, outlining guiding principles, design considerations, and reference architectures for Machine Learning Operations (MLOps). Since.

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Business Analyst Roles and Responsibilities

Knowledge Hut

What is Business Analysis? Change is mandatory in this competitive world, as adapting to new technology to survive or stand out from your competition is essential. Thus, every business has to identify the changes and the factors they need to keep up with to have their hold in the market. That is the task that falls under business analysis. Business analysis is a practice to determine changing business needs and apt solutions.

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Understanding User Needs and Satisfying Them

Speaker: Scott Sehlhorst

We know we want to create products which our customers find to be valuable. Whether we label it as customer-centric or product-led depends on how long we've been doing product management. There are three challenges we face when doing this. The obvious challenge is figuring out what our users need; the non-obvious challenges are in creating a shared understanding of those needs and in sensing if what we're doing is meeting those needs.

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PinCompute: A Kubernetes Backed General Purpose Compute Platform for Pinterest

Pinterest Engineering

Harry Zhang, Jiajun Wang, Yi Li, Shunyao Li, Ming Zong, Haniel Martino, Cathy Lu, Quentin Miao, Hao Jiang, James Wen, David Westbrook | Cloud Runtime Team Image Source: [link] Overview Modern compute platforms are foundational to accelerating innovation and running applications more efficiently. At Pinterest, we are evolving our compute platform to provide an application-centric and fully managed compute API for the 90th percentile of use cases.

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Building Data Pipelines to Create Apps with Large Language Models

KDnuggets

For production grade LLM apps, you need a robust data pipeline. This article talks about the different stages of building a Gen AI data pipeline and what is included in these stages.

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To Tailgate or Not? How Databricks + AccuWeather used ML to answer every football fan's burning question

databricks

Whether you’re an NFL fanatic, an alumnus rooting for your alma mater or a super fan just trying to catch a glimpse of T.

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Decision Tree Analysis in Project Management (with Examples)

Knowledge Hut

While working as a project management professional, you often come across situations where you have to make important decisions for projects with various levels of complexity. There are times when there are several choices, and you will be required to evaluate the outcomes related to each choice and accordingly make decisions that are best for your career and the company as a whole.

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Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You Need to Know

Speaker: Timothy Chan, PhD., Head of Data Science

Are you ready to move beyond the basics and take a deep dive into the cutting-edge techniques that are reshaping the landscape of experimentation? 🌐 From Sequential Testing to Multi-Armed Bandits, Switchback Experiments to Stratified Sampling, Timothy Chan, Data Science Lead, is here to unravel the mysteries of these powerful methodologies that are revolutionizing how we approach testing.

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How to cover up coastal artifacts in mosaiced imagery

ArcGIS

Sometimes mosaiced imagery over water can have undesirable seam artifacts or gaps. Here's one way to make that water look snazzy.

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Data Warehouses vs. Data Lakes vs. Data Marts: Need Help Deciding?

KDnuggets

A comparative overview of data warehouses, data lakes, and data marts to help you make informed decisions on data storage solutions for your data architecture.

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Building Our New Personalized AI-Powered Premium Experience

LinkedIn Engineering

(This article originally appeared on LinkedIn ) Advancements in AI are already starting to transform jobs, skills, and career paths, and we know that our members and customers are thinking about the implications for this new world of work. That’s why I’m excited to share that we’re rolling out a new AI-powered LinkedIn Premium experience , starting with a selected group of US based Premium subscribers today.

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Six Sigma Green Belt vs PMP: What’s the Difference

Knowledge Hut

There are various certifications that professionals can earn to enhance their career growth. Project Management Professional Certification and the Six Sigma certification are two of the most popular certifications in this category. These certifications equip candidates with the necessary knowledge and skills to generate better business outcomes using different approaches.

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How Embedded Analytics Gets You to Market Faster with a SAAS Offering

Start-ups & SMBs launching products quickly must bundle dashboards, reports, & self-service analytics into apps. Customers expect rapid value from your product (time-to-value), data security, and access to advanced capabilities. Traditional Business Intelligence (BI) tools can provide valuable data analysis capabilities, but they have a barrier to entry that can stop small and midsize businesses from capitalizing on them.

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Got five minutes? Get to know ArcGIS GeoEnrichment Service

ArcGIS

ArcGIS GeoEnrichment Service quickly adds information like local demographics, spending patterns, and business data to your study area.

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5 Simple Steps Series: Master Python, SQL, Scikit-learn, PyTorch & Google Cloud

KDnuggets

Dive into KDnuggets Back to Basics: Getting Started in 5 Steps series to help you master Python, SQL, Scikit-learn, PyTorch, and Google Cloud Platform.

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Cybersecurity Lakehouse Best Practices Part 1: Event Timestamp Extraction

databricks

In this four-part blog series "Lessons learned from building Cybersecurity Lakehouses," we will discuss a number of challenges organizations face with data engineering.

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Top 22 Cloud Computing Project Ideas in 2023 [Source Code]

Knowledge Hut

With technological advancements and the need for computing services accelerating heights, many businesses are actively incorporating the cloud for better business operations. Verses the traditional method of storing and managing infrastructure needs, cloud solutions are becoming an efficient way to store, compute and secure resources. As a result, the demand for cloud computing and its applications is immensely high than ever.

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Peak Performance: Continuous Testing & Evaluation of LLM-Based Applications

Speaker: Aarushi Kansal, AI Leader & Author and Tony Karrer, Founder & CTO at Aggregage

Software leaders who are building applications based on Large Language Models (LLMs) often find it a challenge to achieve reliability. It’s no surprise given the non-deterministic nature of LLMs. To effectively create reliable LLM-based (often with RAG) applications, extensive testing and evaluation processes are crucial. This often ends up involving meticulous adjustments to prompts.

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Imagery data sources to power your workflows

ArcGIS

There are many imagery sources available to host your own imagery layers in ArcGIS Image for ArcGIS Online.

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Novice to Ninja: Why Your Python Skills Matter in Data Science

KDnuggets

As a data scientist, is it worthwhile leveling up your Python skills? Dive into code comparisons across expertise levels & discover if "good enough" is really enough.

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Nurturing Engineering Talent: The DoorDash Apprentice Engineering Manager Program 

DoorDash Engineering

At DoorDash, the growth and development of our engineering talent is critical to our success and ability to continue innovating. Apprenticeship has had a long history of successfully cultivating new generations of talent across many different industries. Tech is no different. Designed to identify and foster exceptional engineering talent within the company, DoorDash’s Apprentice Engineering Manager Program prepares engineers to transition into a people management role effectively and autonomousl

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Managed Detection & Response Leaders Embrace Data and Analytics to Stay Ahead

Snowflake

The Managed Detection & Response (MDR) industry finds itself in a new era with unprecedented challenges from platform giants and the migration of the attack surface to the cloud, with innovation becoming a requirement for survival. Companies built to provide clients with 24×7 “eyes on glass” now find themselves at the intersection of rapid technological advancements and evolving threat landscapes.

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From Developer Experience to Product Experience: How a Shared Focus Fuels Product Success

Speaker: Anne Steiner and David Laribee

As a concept, Developer Experience (DX) has gained significant attention in the tech industry. It emphasizes engineers’ efficiency and satisfaction during the product development process. As product managers, we need to understand how a good DX can contribute not only to the well-being of our development teams but also to the broader objectives of product success and customer satisfaction.