Snowflake

JANUARY 16, 2025

You can learn more in our SwiftKV research blog post. We are also making knowledge distillation pipelines via ArcticTraining Framework open source so you can build your own SwiftKV models for your enterprise or academic needs. We are helping them build gen AI solutions that are both cost effective and high performing.

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Algorithm Data Analysis Building Process 97

Pinterest Engineering

SEPTEMBER 20, 2023

These teams work together to ensure algorithmic fairness, inclusive design, and representation are an integral part of our platform and product experience. Our commitment is evidenced by our history of building products that champion inclusivity. “Everyone” has been the north star for our Inclusive AI and Inclusive Product teams.

Building 109

Building Pipeline-centric Machine Learning Datasets 109

Cloudera

JANUARY 9, 2025

Its about comprehensive solutions, not isolated algorithms. Executives, data teams, and even end-users understand that AI means more than building models; it means unlocking strategic value. Lets build the future of enterprise intelligencetogether. Within it, youll find capabilities that clearly map to what they deliver.

Machine Learning 85

Machine Learning Raw Data Government Algorithm 85

Cloudera

DECEMBER 1, 2023

It focuses on five key pillars: investing in research and development; unleashing government AI resources; setting standards and policy; building the AI workforce; and advancing trust and security. The post Building Trust in Public Sector AI Starts with Trusting Your Data appeared first on Cloudera Blog.

Building 109

Building Government Transportation Data Governance 109

Edureka

APRIL 22, 2025

This blog will explore the significant advancements, challenges, and opportunities impacting data engineering in 2025, highlighting the increasing importance for companies to stay updated. In 2025, this blog will discuss the most important data engineering trends, problems, and opportunities that companies should be aware of.

Data Engineering 52

Data Engineering Data Engineer Engineering Consulting 52

Data Engineering Podcast

DECEMBER 7, 2020

Summary Building data products are complicated by the fact that there are so many different stakeholders with competing goals and priorities. When you’re ready to build your next pipeline, or want to test out the projects you hear about on the show, you’ll need somewhere to deploy it, so check out our friends at Linode.

Building 100

Building Big Data Consulting Data Engineering 100

Scott Logic

OCTOBER 24, 2024

Our most interesting mission, in my opinion, was to design and build an algorithm that assigned talks to attendees according to their choices. This algorithm would save organisers the time, human error and brain power required to ensure all attendees are fairly allocated. And how can we do this over the course of multiple slots?

Algorithm 52

Algorithm Building Designing IT 52

LinkedIn Engineering

DECEMBER 20, 2023

At LinkedIn, trust is the cornerstone for building meaningful connections and professional relationships. By leveraging cutting-edge technologies, machine learning algorithms, and a dedicated team, we remain committed to ensuring a secure and trustworthy space for professionals to connect, share insights, and foster their career journeys.

Building 91

Building Algorithm Kafka Machine Learning 91

Snowflake

DECEMBER 11, 2023

While digital advertisers and paid media professionals are on the hook to build ample sales pipeline and maximize return on ad spend (ROAS), they’re also expected to deliver personalized advertising content while navigating evolving privacy requirements and adhering to consumer expectations—all while extracting insights from siloed ad platforms.

Building 105

Building Cloud Media Algorithm 105

Netflix Tech

JUNE 1, 2023

To do this, we devised a novel way to simulate the projected traffic weeks ahead of launch by building upon the traffic migration framework described here. We used this simulation to help us surface problems of scale and validate our Ads algorithms. Basic with ads was launched worldwide on November 3rd.

Algorithm 139

Algorithm Kafka Metadata Systems 139

DareData

JUNE 11, 2024

With its capabilities of efficiently training deep learning models (with GPU-ready features), it has become a machine learning engineer and data scientist’s best friend when it comes to train complex neural network algorithms. In this blog post, we are finally going to bring out the big guns and train our first computer vision algorithm.

Algorithm 52

Algorithm Datasets Deep Learning Architecture 52

Workfall

FEBRUARY 7, 2023

With the introduction of WebAssembly, it became possible to build frontend web apps in Rust , such as the one we just built, expanding development opportunities for developers. In case you need to install, you can refer to our Rust blog. We will come up with more such use cases in our upcoming blogs.

Building 87

Building PostgreSQL Coding AWS 87

Team Data Science

MAY 20, 2020

In this blog post only two of the four phases will be discussed. A data scientist who can work on algorithms. The Minimum Viable Product Phase (MVP) In the next phase, the MVP phase, you will build a Minimum Viable Product with a minimum of support for the business idea. But now from the beginning.

Data Science 130

Data Science Algorithm Data Engineering Data Engineer 130

Cloudera

MAY 27, 2021

This blog post was written by Pedro Pereira as a guest author for Cloudera. . It’s important to be conscious of this reality when creating algorithms and training models. Big data algorithms are smart, but not smart enough to solve inherently human problems. AI and other data-intensive algorithms are infants.

Algorithm 119

Algorithm Media Consulting Machine Learning 119

Pinterest Engineering

JANUARY 31, 2025

This work illustrates our effort in successfully building Pinterest an internal embedding-based retrieval system for organic content learned purely from logged user engagement events and serves in production. At Pinterest, we have our in-house ANN serving system designed based on algorithms [5, 7].

Systems 67

Systems Metadata Machine Learning Architecture 67

Netflix Tech

OCTOBER 12, 2022

We had a fun conversation with his team, and we realized that some parts of it might make a good blog post as well. So we jointly edited a bit for length and clarity, and are posting here as well as on OfferFit’s blog. And so I did that and spent some time building out search algorithms and recommendation engines at Yelp.

Building 79

Building Designing Management Algorithm 79

LinkedIn Engineering

MARCH 21, 2023

One of the most exciting parts of our work is that we get to play a part in helping progress a skills-first labor market through our team’s ongoing engineering work in building our Skills Graph. soft or hard skill), descriptions of the skill (“the study of computer algorithms…”), and more.

Building 85

Building Recruitment Machine Learning Deep Learning 85

Edureka

NOVEMBER 28, 2023

OpenCV was build to provide a common infrastructure for computer vision applications and to accelerate the use of machine perception in the commercial products. In this blog, we will learn how we can install OpenCV python on windows. Shape Analysis – The module shape provides the algorithms to extract various shapes.

Python 98

Python Algorithm Machine Learning Programming Language 98

Data Engineering Weekly

FEBRUARY 9, 2025

I found the product blog from QuantumBlack gives a view of data quality in unstructured data. The blog post highlights the industry trend of search engines transitioning towards embedding-based systems, moving beyond traditional IDF models. The system design is an excellent reminder of thinking from a user's perspective.

Data Engineering 59

Data Engineering Data Engineer Engineering Unstructured Data 59

Cloudera

NOVEMBER 17, 2021

In the hands of an experienced practitioner, AutoML holds much promise for automating away some of the tedious parts of building machine learning systems. TPOT is a library for performing sophisticated search over whole ML pipelines, selecting preprocessing steps and algorithm hyperparameters to optimize for your use case.

Machine Learning 124

Machine Learning Algorithm Data Science Retail 124

Knowledge Hut

MARCH 22, 2024

The C programming language plays a crucial role in Data Structure and Algorithm (DSA). Since C is a low-level language, it allows for direct memory manipulation, which makes it perfect for implementing complex data structures and algorithms efficiently. This blog will provide you with a strong foundation in DSA using C.

Algorithm 52

Algorithm Programming Language Software Engineer Software Engineering 52

Netflix Tech

NOVEMBER 11, 2022

This blog series will take you behind the scenes, showing you how we use the power of machine learning to create stunning media at a global scale. With media-focused ML algorithms, we’ve brought science and art together to revolutionize how content is made. Media is at the heart of Netflix.

Media 98

Media Machine Learning Algorithm Deep Learning 98

Cloudera

FEBRUARY 11, 2022

Advances in the development and application of Machine Learning (ML) and Deep Learning (DL) algorithms, require greater care to ensure that the ethics embedded in previous rule-based systems are not lost. This blog post hopes to provide this foundational understanding. What is Machine Learning. Figure 03: The Data Science Lifecycle.

Machine Learning 97

Machine Learning Algorithm Data Science Government 97

Christophe Blefari

MARCH 22, 2024

❤️ I rarely say it, if Data News helps you save time you should consider taking a paid subscription (60€/year) to help me covers the blog fees and my writing Fridays. On my side I'll talk about Apache Superset and what you can do to build a complete application with it. on April 10. Now give me the news.

Electronics 130

Electronics Media Data Python 130

Cloudera

NOVEMBER 19, 2020

Machine learning algorithms enable fraud detection systems to distinguish between legitimate and fraudulent behaviors. Some of these algorithms can be adaptive to quickly update the model to take into account new, previously unseen fraud tactics allowing for dynamic rule adjustment. A better approach is needed.

Government 119

Government Machine Learning Algorithm Raw Data 119

Cloudera

JULY 27, 2021

We believe the best way to learn what a technology is capable of is to build things with it. Only through hands-on experimentation can we discern truly useful new algorithmic capabilities from hype. Some examples of our recent experiments: Building a natural language question answering interface to Wikipedia.

Data Science 117

Data Science Machine Learning Python Deep Learning 117

Netflix Tech

JANUARY 25, 2023

An example for storing both time and space based data would be an ML algorithm that can identify characters in a frame and wants to store the following for a video In a particular frame (time) In some area in image (space) A character name (annotation data) Pic 1 : Editors requesting changes by drawing shapes like the blue circle shown above.

Algorithm 116

Algorithm Media Metadata Data Ingestion 116

Rockset

MARCH 18, 2024

In this blog, we’ll discuss how RAG fits into the paradigm of real-time data processing and show an example product recommendation application using both Kafka and Flink on Confluent Cloud together with Rockset. Building a real-time, contextual and trustworthy knowledge base for AI applications revolves around RAG pipelines.

Cloud 64

Cloud Building Metadata Kafka 64

Tweag

MARCH 6, 2024

Three years ago, a blog post introduced destination-passing style (DPS) programming in Haskell, focusing on array processing, for which the API was made safe thanks to Linear Haskell. The present blog post is mostly based on my recent paper Destination-passing style programming: a Haskell implementation , published at JFLA 2024.

Programming 132

Programming Data Programming Language Coding 132

Netflix Tech

JANUARY 30, 2023

In a previous blog post we explained how our artwork personalization algorithm can pick the best image for each member, but how do we create a good set of images to choose from? In this blog post, we talk about two approaches to create effective artwork. What data would you like to have if you were designing an asset suite?

Algorithm 105

Algorithm Media Machine Learning Designing 105

Cloudera

NOVEMBER 25, 2021

Advances in the performance and capability of Artificial Intelligence (AI) algorithms has led to a significant increase in adoption in recent years. Ethical AI is a multi-disciplinary effort to design and build AI systems that are fair and improve our lives. So why is it so hard to build ethical systems? Find out more.

Government 98

Government Insurance Algorithm Machine Learning 98

Christophe Blefari

APRIL 19, 2024

Structured generative AI — Oren explains how you can constraint generative algorithms to produce structured outputs (like JSON or SQL—seen as an AST). This blog shows how you can use Gen AI to evaluate inputs like translations with added reasons. — A great blog to answer a great question.

MySQL 130

MySQL Data Datasets SQL 130

Cloudera

JULY 20, 2021

Build your data strategy around the convergence of software and hardware. Build your data strategy around relevant data, not last years data because it’s easy to access. Everyone’s algorithms are off, some examples: Retail’s fulfillment ability. Airline schedules and pricing algorithms.

Retail 106

Retail Telecommunication Manufacturing Insurance 106

Netflix Tech

JANUARY 10, 2024

This introductory blog focuses on an overview of our journey. Future blogs will provide deeper dives into each service, sharing insights and lessons learned from this process. Finally, relevant abstractions allow media algorithm developers to focus on the manipulation of video and audio signals rather than on infrastructural concerns.

Process 95

Process Pipeline-centric Media Metadata 95

AltexSoft

AUGUST 25, 2021

Tools you can use to build NLP models. But today’s programs, armed with machine learning and deep learning algorithms, go beyond picking the right line in reply, and help with many text and speech processing problems. In NLP tasks, this process is called building a corpus. Keep reading to learn: What problems NLP can help solve.

Process 139

Process Deep Learning Datasets Machine Learning 139

U-Next

MARCH 1, 2023

You can find many Artificial Intelligence applications in this blog that you can use as project ideas for your academic assignments or personal growth. These bots employ AI algorithms to comprehend customer questions about credit cards, accounts, and loans. You must create an algorithm to ascertain how many units are sold every day.

Project 96

Project Medical Banking Healthcare 96

Confluent

AUGUST 29, 2019

We will cover how you can use them to enrich and visualize your data, add value to it with powerful graph algorithms, and then send the result right back to Kafka. All of the code and setup discussed in this blog post can be found in this GitHub repository , so you can try it yourself! Link prediction algorithms.

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Kafka Process Algorithm Cloud 55