Sat.Jun 17, 2023 - Fri.Jun 23, 2023

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Google Domains to shut down

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 one out of five topics from today’s subscriber-only The Scoop issue. To get full issues twice a week, subscribe here.

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Modern Data Engineering with MAGE: Empowering Efficient Data Processing

Analytics Vidhya

Introduction In today’s data-driven world, organizations across industries are dealing with massive volumes of data, complex pipelines, and the need for efficient data processing. Traditional data engineering solutions, such as Apache Airflow, have played an important role in orchestrating and controlling data operations in order to tackle these difficulties.

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What's new in Apache Spark 3.4.0 - shuffle changes

Waitingforcode

Shuffle is a permanent point in the What's new in Apache Spark series. Why? It's often one the most time consuming part of the jobs and knowing the improvement simply helps writing better pipelines.

IT 130
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Old Dog Learn New Tricks? Starburst (Trino) Galaxy and other thoughts.

Confessions of a Data Guy

Sometimes I think Data Engineering is the same as it was 10+ years ago when I started doing it, and sometimes I think everything has changed. It’s probably both. In some ways, the underlying concepts have not moved an inch, some certain truths and axioms still rule over us all like some distant landlord, requiring […] The post Old Dog Learn New Tricks?

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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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New Approaches For Detecting AI-Generated Profile Photos

LinkedIn Engineering

Co-authors: Shivansh Mundra , Gonzalo Aniano Porcile , Smit Marvaniya , Hany Farid A core part of what we do on the Trust Data Team at LinkedIn is create, deploy, and maintain models that detect and prevent many types of abuse. This spans the detection and prevention of fake accounts, account takeovers, and policy-violating content. We are constantly working to improve and increase the effectiveness of our anti-abuse defenses to protect the experiences of our members and customers.

Media 132
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A Practical Guide to Transfer Learning using PyTorch

KDnuggets

In this article, we’ll learn to adapt pre-trained models to custom classification tasks using a technique called transfer learning. We will demonstrate it for an image classification task using PyTorch, and compare transfer learning on 3 pre-trained models, Vgg16, ResNet50, and ResNet152.

IT 113

More Trending

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Conceptual Introduction to Delta Lake.

Confessions of a Data Guy

The post Conceptual Introduction to Delta Lake. appeared first on Confessions of a Data Guy.

Data 130
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Announcing Cadence 1.0: The Powerful Workflow Platform Built for Scale and Reliability

Uber Engineering

We are excited to release Cadence 1.0! Used by many major companies, at Uber it powers over 1,000 services with 100K+ updates a second. Learn how Cadence makes it easy to build complex distributed systems.

Systems 97
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Orca LLM: Simulating the Reasoning Processes of ChatGPT

KDnuggets

Orca is a 13B parameter model that learns to imitate the reasoning processes of LFMs. It uses progressive learning and teacher assistance from ChatGPT to overcome capacity gaps. By leveraging rich signals from GPT-4, Orca enhances its capabilities and improves imitation learning performance.

Process 112
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How Databricks’ Lakehouse is helping to power a new era for TD Bank Group's Data Transformation

databricks

This blog is the first of a 3-part series chronicling TD Bank's Data Platform transformation and the enablement of their Data as a.

Banking 103
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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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The Docker Compose of ETL: Meerschaum Compose

Towards Data Science

Photo by CHUTTERSNAP on Unsplash This article is about Meerschaum Compose , a tool for defining ETL pipelines in YAML and a plugin for the data engineering framework Meerschaum. Docker was a game-changer, revolutionizing the way we design, build, and run our cloud applications. Pretty early on, however, developers realized its flexibility made collaboration difficult, so docker-compose became to the tool of choice for managing environments and multi-container projects.

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Cybersecurity Professionals: The Unsung Superheroes of the Digital World

LinkedIn Engineering

In a world where superheroes captivate our imaginations, it's sometimes hard to recognize the real-life superheroes among us like intelligence analysts, forensic scientists, and cybersecurity professionals. Yes, cybersecurity professionals! Though we may not wear capes or possess extraordinary powers, our role, especially here at LinkedIn, is crucial in safeguarding our members, customers, and employees from the ever-present threat of cyberattacks.

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Closing the Gap Between Human Understanding and Machine Learning: Explainable AI as a Solution

KDnuggets

This article elaborates on the importance of Explainable AI (XAI), what the challenges in building interpretable AI models are, and some practical guidelines for companies to build XAI models.

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GIS and BIM/CAD at the Esri User Conference 2023

ArcGIS

Check out exciting sessions, special interest groups and activities on BIM, CAD, and GIS integrations featured at Esri UC 2023.

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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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Databricks on AWS Guide to Data + AI Summit 2023 featuring Labcorp, Conde Nast, Grammarly, Vizio, NTT Data, Impetus, Amgen, and YipitData

databricks

This is a collaborative post from Databricks and Amazon Web Services (AWS). We thank Venkat Viswanathan, Data and Analytics Strategy Leader, Partner Solutions.

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Do You Know Where All Your Data Is?

Cloudera

In spite of diligent digital transformation efforts, most financial services institutions still support a loose patchwork of siloed systems and repositories. These dis-integrated resources are “data platforms” in name only: in addition to their high maintenance costs, their lack of interoperability with other critical systems makes it difficult to respond to business change.

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Making Predictions: A Beginner’s Guide to Linear Regression in Python

KDnuggets

Learn everything about the most popular Machine Learning algorithm, Linear Regression, with its Mathematical Intuition and Python implementation.

Python 114
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Startup Spotlight: Dassana and the Future of Security Control Effectiveness Reporting

Snowflake

Welcome to Snowflake’s Startup Spotlight, where we learn about awesome companies building businesses on Snowflake. In this edition, we’re digging into cybersecurity with Parth Shah, Co-Founder and Head of Product at Dassana , as he discusses the power of operationalizing security data, why you need to consider security data lakes, and how Snowflake gave Dassana an agility upgrade.

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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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Advancing Business with Data & AI: Announcing the Finalists for the 2023 Databricks Data Team Transformation Award

databricks

The annual Data Team Awards showcase how different enterprise data teams are delivering solutions to some of the world’s toughest problems. Nearly 300 n.

Data 81
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Q&A—How Wealthsimple Builds API Financial Solutions with Confluent

Confluent

See why Wealthsimple chose Confluent to build real-time API financial solutions that could process, transform, and govern real-time data for downstream systems.

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What are Vector Databases and Why Are They Important for LLMs?

KDnuggets

Large language models (LLMs) currently have the AI world in a chokehold. It is essential to understand why vector databases are important to LLMs.

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Join Snowflake’s Media Data Cloud Revolution at Cannes Lions 2023

Snowflake

It’s snowing on la croisette ! Snowflake is back again for another exciting year at Cannes Lions. The Cannes Lions Festival of Creativity, June 18–23, is the premiere media and entertainment industry event, bringing together legends, innovators, and thought leaders from around the globe. Simply put, it’s where people and organizations showcase what’s new, what’s next, and push the boundaries of what’s possible in the industry.

Media 57
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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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Build governed pipelines with Delta Live Tables and Unity Catalog

databricks

We are excited to announce the public preview of Unity Catalog support for Delta Live Tables (DLT). With this preview, any data team.

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Fine-tune MPT-7B on Amazon SageMaker

Towards Data Science

Learn how to prepare a dataset and create a training job to fine-tune MPT-7B on Amazon SageMaker Continue reading on Towards Data Science »

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From Unstructured to Structured Data with LLMs

KDnuggets

Learn how to use large language models to extract insights from documents for analytics and ML at scale. Join this webinar and live tutorial to learn how to get started.

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How to Rapidly Add & Manage Cloud Data Sources

Acceldata

Learn how to add and manage cloud data sources -- for sources like Snowflake, Databricks, Amazon S3, RedShift, BigQuery, and others -- to the Acceldata Data Observability Cloud.

Cloud 52
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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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Accelerating Innovation at JetBlue Using Databricks

databricks

This blog is authored by Sai Ravuru Senior Manager of Data Science & Analytics at JetBlue The role of data in the aviation.

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How Security Vulnerabilities are Reported & Handled in Apache Superset

Preset

All the things you might want to know about how Superset tracks and tackles security concerns as a project of Apache Software Foundation, and how Preset fits into that process.

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More Free Courses on Large Language Models

KDnuggets

Interested in learning about large language models? Get up and running with these free courses from DeepLearning.AI, Google Cloud, Udacity, and more.

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How Extend Leverages Confluent's Data Streaming Platform for Backend Communications

Confluent

Discover how Extend leveraged Confluent's data streaming platform and AWS to streamline backend communication and embrace an event-driven architecture.

AWS 57
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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.