Robinhood

FEBRUARY 7, 2024

Together, we are building products and services that help create a financial system everyone can participate in. When dealing with large-scale data, we turn to batch processing with distributed systems to complete high-volume jobs. Why Batch Processing is Integral to Robinhood Why is batch processing important?

Process 75

Process Hadoop Architecture Accessible 75

Precisely

SEPTEMBER 25, 2023

An important part of this journey is the data validation and enrichment process. Defining Data Validation and Enrichment Processes Before we explore the benefits of data validation and enrichment and how these processes support the data you need for powerful decision-making, let’s define each term.

Data Validation 98

Data Validation Process Raw Data Data Cleanse 98

Towards Data Science

NOVEMBER 16, 2023

Data Management A tutorial on how to use VDK to perform batch data processing Photo by Mika Baumeister on Unsplash Versatile Data Ki t (VDK) is an open-source data ingestion and processing framework designed to simplify data management complexities. ELT (Extract, Load, Transform) is a typical use case for batch data processing.

Data Process 75

Data Process Process Raw Data Data 75

Pinterest Engineering

JANUARY 4, 2024

In order to build a distributed and replicated service using RocksDB, we built a real time replicator library: Rocksplicator. Maintaining these disparate systems and building common functionality among them was adding a huge overhead to the teams. Individual rows constitute a dataset. RocksDB is a single node key value store.

Database 78

Database Building Datasets Relational Database 78

LinkedIn Engineering

JANUARY 19, 2024

This multi-entity handover process involves huge amounts of data updating and cloning. Data consistency, feature reliability, processing scalability, and end-to-end observability are key drivers to ensuring business as usual (zero disruptions) and a cohesive customer experience. Push for eventual success of the request.

Recruitment 88

Recruitment Data Process Process Kafka 88

Knowledge Hut

FEBRUARY 1, 2024

While building predictive models, if your results aren’t satisfactory, then the two things that can go wrong are data or models. You can try some hands-on with online datasets to gain practical exposure. Data cleaning is the process of identifying and fixing incorrect data. Then comes the data format.

Data Science 52

Data Science Process Data Cleanse Datasets 52

LinkedIn Engineering

DECEMBER 20, 2023

At LinkedIn, trust is the cornerstone for building meaningful connections and professional relationships. Let’s look into the critical modules that are needed to build this type of system. We need systems to ingest, process, and analyze the data efficiently.

Building 91

Building Algorithm Kafka Machine Learning 91

Pinterest Engineering

SEPTEMBER 20, 2023

Our commitment is evidenced by our history of building products that champion inclusivity. We know from experience that building for marginalized communities helps make the product work better for everyone. Signal Development and Indexing The process of developing our visual body type signal essentially begins with data collection.

Building 85

Building Pipeline-centric Machine Learning Datasets 85

Rockset

MAY 21, 2024

Secondly, as LLMs are trained on datasets that are static and often outdated by the time they're deployed, they are unable to provide accurate or relevant information about recent developments or trends. Computational Complexity: Requires efficient retrieval mechanisms to handle large-scale datasets in real-time. What is Self-RAG?

Building 52

Building Utilities Datasets Database 52

Knowledge Hut

JULY 28, 2023

Data Labeling is the process of assigning meaningful tags or annotations to raw data, typically in the form of text, images, audio, or video. In the world of Supervised Machine Learning, the models train using the samples of “labelled” datasets. You can break down the data labeling process in the below logical order: 1.

Machine Learning 52

Machine Learning Process Datasets Raw Data 52

Rockset

MARCH 18, 2024

Flink is one of the most popular stream processing technologies, ranked as a top five Apache project and backed by a diverse committer community including Alibaba and Apple. It powers steam processing at many companies including Uber, Netflix, and Linkedin. What are the challenges building RAG pipelines?

Cloud 64

Cloud Building Metadata Kafka 64

Christophe Blefari

MARCH 15, 2024

Building Meta’s GenAI infrastructure — 2x 24k GPU clusters and it's growing. Arroyo, a stream-processing platform, rebuilt their engine using DataFusion. The devil is in the details and when it comes to data pipelines there are a lot of details, which often refrain us to buy leading to build (or code).

Metadata 272

Metadata Datasets Data Data Warehouse 272

AltexSoft

AUGUST 25, 2021

And this technology of Natural Language Processing is available to all businesses. Available methods for text processing and which one to choose. Tools you can use to build NLP models. What is Natural Language Processing? Here are some big text processing types and how they can be applied in real life.

Process 139

Process Deep Learning Datasets Machine Learning 139

LinkedIn Engineering

MARCH 23, 2023

Co-Authors: Yuhong Cheng , Shangjin Zhang , Xinyu Liu, and Yi Pan Efficient data processing is crucial in reducing learning curves, simplifying maintenance efforts, and decreasing operational complexity. By unifying these pipelines, we have saved 94% of processing time. Samza , Spark and Apache Flink ).

Process 97

Process Lambda Architecture Kafka Datasets 97

AltexSoft

OCTOBER 18, 2022

In this post, we’ll briefly discuss challenges you face when working with medical data and make an overview of publucly available healthcare datasets, along with practical tasks they help solve. At the same time, de-identification only encrypts personal details and hides them in separate datasets. Medical datasets comparison chart .

Medical 52

Medical Datasets Machine Learning Hospitality 52

Knowledge Hut

MARCH 22, 2024

Reverse engineering software is the process of dissecting it to understand its components, functionality, and workflow without having access to the source code. 5 Steps of Reverse Engineering [Process] The process of reverse engineering can be broken down into five key steps. What is Reverse Engineering in Software Engineering?

Process 52

Process Engineering Electronics Software Engineer 52

Monte Carlo

APRIL 16, 2024

How do you build data quality standards – and how do you measure and maintain them? Knowing the right data quality metrics is imperative to building trust with downstream consumers and stakeholders. That helps build trust,” says Samiksha. Reliability is the first step to unlocking real value from your data. Stefanie agrees. “We

Process 52

Process Government Data Data Engineering 52

Towards Data Science

MARCH 9, 2023

Datasets containing attributes of Airbnb listings in 10 European cities ¹ will be used to create the same Pipeline in scikit-learn and MLLib. The Pipeline will manipulate the numerical and categorical features in the pre-processing stage before applying a Random Forest Regressor to generate price predictions for the listings.

Machine Learning 75

Machine Learning Building Datasets Scala 75

DareData

DECEMBER 16, 2023

Tensors are the backbone of deep learning models so naturally we can use them to fit simpler machine learning models to our datasets. In the process, we’ll learn about torch Optimizers, Weights and other parameters of our learning model, something that will be extremely useful for more complex architectures. Let’s start!

Building 52

Building Deep Learning Datasets Coding 52

Data Engineering Podcast

NOVEMBER 20, 2021

With the improvements in streaming engines it is now possible to perform all of your data integration in near real time, but it can be challenging to understand the proper processing patterns to make that performant. The batch model for processing is intuitive despite its latency problems. What are the benefits that it provides?

Data Lake 100

Data Lake Data Integration Lambda Architecture Process 100

Netflix Tech

OCTOBER 16, 2019

By Ammar Khaku Introduction In a microservice architecture such as Netflix’s, propagating datasets from a single source to multiple downstream destinations can be challenging. One example displaying the need for dataset propagation: at any given time Netflix runs a very large number of A/B tests.

Datasets 75

Datasets Metadata Bytes Machine Learning 75

Striim

NOVEMBER 17, 2023

Real-time data processing in the world of machine learning allows data scientists and engineers to focus on model development and monitoring. Specifically, in this dataset, 1 represents “setosa,” 2 represents “versicolor,” and 3 represents “virginica.”

Machine Learning 52

Machine Learning Data Process PostgreSQL Process 52

Lyft Engineering

APRIL 21, 2023

Building a large scale unsupervised model anomaly detection system — Part 1 Distributed Profiling of Model Inference Logs By Anindya Saha , Han Wang , Rajeev Prabhakar Introduction LyftLearn is Lyft’s ML Platform. We can unify data from totally different models and process them using the same pipeline in the following step.

Systems 105

Systems Building Machine Learning Datasets 105

Tweag

APRIL 19, 2023

To allow innovation in medical imaging with AI, we need efficient and affordable ways to store and process these WSIs at scale. A single hospital makes many captures a day, producing terabytes of such data to store and process. Much like Spark, its module ray.data is focused on loading and processing data as scale. width , spec.

Medical 60

Medical Process Cloud Bytes 60

Databand.ai

AUGUST 30, 2023

Building a Winning Data Quality Strategy: Step by Step Eitan Chazbani August 30, 2023 What Is a Data Quality Strategy? A data quality strategy details the processes, tools, and techniques employed to ensure your company’s data is accurate, consistent, complete, and up-to-date.

Building 52

Building Data Cleanse Data Governance Datasets 52

AltexSoft

MAY 12, 2022

Our brains are constantly processing sounds to give us important information about our environment. Audio analysis is a process of transforming, exploring, and interpreting audio signals recorded by digital devices. Source: Audio Singal Processing for Machine Learning. What is audio analysis? Speech recognition.

Machine Learning 122

Machine Learning Building Datasets Healthcare 122

Towards Data Science

AUGUST 2, 2023

A Step-by-Step Guide to Building an Effective Data Quality Strategy from Scratch How to build an interpretable data quality framework based on user expectations Photo by Rémi Müller on Unsplash As data engineers, we are (or should be) responsible for the quality of the data we provide. How much should we worry about data quality?

Building 98

Building Data Consolidation Data Datasets 98

Precisely

JULY 25, 2023

Organizations that run SAP can use Excel-to-SAP automation to do more with less, while also increasing agility and improving their SAP master data management process automation. We bring automation closer to the business users who own the data and the day-to-day processes that drive the business. That’s bad for the business.

Data Process 52

Data Process Process Data Data Integration 52

Towards Data Science

FEBRUARY 19, 2024

Image from Unsplash Building a Semantic Book Search: Scale an Embedding Pipeline with Apache Spark and AWS EMR Serverless Using OpenAI’s Clip model to support natural language search on a collection of 70k book covers In a previous post I did a little PoC to see if I could use OpenAI’s Clip model to build a semantic book search.

AWS 59

AWS Building Bytes Python 59

Towards Data Science

MARCH 29, 2023

Turbo and GPT-4 to categorize datasets without the need for labeled data or model training, by prompting the model with data excerpts and category definitions. Especially useful was that the model could provide reasoning for its predictions which helped to identify improvements to the process. Is the Dataset in an Approved Category?

Datasets 62

Datasets Food Retail Hospitality 62

Knowledge Hut

JUNE 20, 2023

Natural Language Processing (NLP) has been a buzzword in the tech industry. In this article, we will explore the various NLP career opportunities and the skills and qualifications required to land Natural Language Processing positions. What is Natural Language Processing? Searching The same as in search engines.

Process 52

Process Computer Science Algorithm Education 52

Knowledge Hut

MAY 3, 2024

Types of Machine Learning: Machine Learning can broadly be classified into three types: Supervised Learning: If the available dataset has predefined features and labels, on which the machine learning models are trained, then the type of learning is known as Supervised Machine Learning. A sample of the dataset is shown below.

Machine Learning 98

Machine Learning Algorithm Datasets Medical 98

ProjectPro

JANUARY 15, 2021

And honestly, there are a lot of real-world machine learning datasets around you that you can opt to start practicing your fundamental data science and machine learning skills, even without having to complete a comprehensive data science or machine learning course. Table of Contents What is a dataset in machine learning?

Datasets 40

Datasets Machine Learning Retail Banking 40

Monte Carlo

JANUARY 29, 2024

Multiple stakeholders from multiple teams swinging wildly at whatever pops up from the incident hole—and occasionally hitting each other in the process. That makes the need for a data incident management process inevitable as well. The same should be true of your incident management process.

Process 69

Process Management IT Data 69

Snowflake

APRIL 20, 2023

Snowflake users are already taking advantage of LLMs to build really cool apps with integrations to web-hosted LLM APIs using external functions , and using Streamlit as an interactive front end for LLM-powered apps such as AI plagiarism detection , AI assistant , and MathGPT. Join us in Vegas at our Summit to learn more.

Building 117

Building Unstructured Data Government Coding 117

Precisely

FEBRUARY 27, 2023

To use it effectively, organizations must invest in the people, processes, and technology that enable users throughout the organization to make sound business decisions based on trusted data. By automating repetitive processes, organizations can free up their valuable human resources to focus on higher value activities.

Process 52

Process Finance Datasets Designing 52

Rockset

MARCH 28, 2024

Overview In this guide, you will: Gain a high-level understanding of vectors, embeddings, vector search, and vector databases, which will clarify the concepts we will build upon. Build a dynamic web application using vanilla CSS, HTML, JavaScript, and Flask, seamlessly integrating with the Rockset API and the OpenAI API.

Systems 52

Systems Building Database Utilities 52