Rockset

MARCH 31, 2021

Ritual started in 2016 with a single reimagined multivitamin for women and has since launched products for different stages of her life and seen tremendous growth, crossing the threshold of over 1M multivitamin bottle sales in 2019. Ritual’s data stack for serving personalized cart recommendations, email campaigns and banner ads.

Food 40

Food Data Science SQL Data Warehouse 40

AltexSoft

MAY 12, 2021

In this article, we’ll share key take-aways from our recent experience in building a prototype of a decision support tool that performs three tasks: lung segmentation, pneumothorax detection and localization, and. Otherwise, let’s proceed to the first and most fundamental step in building AI-fueled computer vision tools — data preparation.

Medical 72

Medical Healthcare Datasets Machine Learning 72

U-Next

SEPTEMBER 22, 2022

Predictive modeling projects require historical data to identify patterns and trends. Predictions are essential for businesses today because they can find better ways to serve the market, build better products, and reduce operational costs. . Many data warehouses are not directly connected to systems that store user data.

Hospitality 40

Hospitality Algorithm Machine Learning Banking 40

ProjectPro

JANUARY 19, 2022

Read this blog till the end to learn more about the roles and responsibilities, necessary skillsets, average salaries, and various important certifications that will help you build a successful career as an Azure Data Engineer. The big data industry is flourishing, particularly in light of the pandemic's rapid digitalization.

Data Engineer 52

Data Engineer Data Engineering Engineering Data Storage 52

Netflix Tech

OCTOBER 18, 2019

theme of the ML Platform meetup hosted at Netflix, Los Gatos on Sep 12, 2019. Finally, Elliot ended by talking about some of the challenges in building this Bandit framework. He also talked about common pitfalls of stream-processed data like out of order processing.

Algorithm 51

Algorithm Architecture Machine Learning Deep Learning 51

AltexSoft

MAY 14, 2021

Data generated from various sources including sensors, log files and social media, you name it, can be utilized both independently and as a supplement to existing transactional data many organizations already have at hand. Talend is considered one of the most effective and easy-to-use data integration tools focusing on Big Data.

Big Data 78

Big Data Data Analytics IT NoSQL 78

ProjectPro

JANUARY 15, 2021

The “transaction-id” column in the events data file has a value only if a transaction is made by the user else it will be N/A. Download Freiburg Groceries Dataset Computer Vision Project Ideas using Freiburg Groceries Dataset You can build a computer vision model based on multi-class object classification for grocery products.

Machine Learning 40

Machine Learning Datasets Retail Banking 40

ProjectPro

MAY 18, 2016

from 2014-2019. “Customers building their outward facing Web and mobile applications on public clouds while trying to build Hadoop applications on-premises should evaluate vendors offering it as-a-service. Data scientists should be able to run Hadoop jobs through Pig, Hive , Mahout and other data science programming tools.

Hadoop 40

Hadoop Google Cloud Big Data Cloud Computing 40

Netflix Tech

OCTOBER 18, 2019

theme of the ML Platform meetup hosted at Netflix, Los Gatos on Sep 12, 2019. Finally, Elliot ended by talking about some of the challenges in building this Bandit framework. He also talked about common pitfalls of stream-processed data like out of order processing.

Algorithm 40

Algorithm Architecture Machine Learning Deep Learning 40

KDnuggets

NOVEMBER 21, 2019

This blog shows how text data representations can be used to build a classifier to predict a developer’s deep learning framework of choice based on the code that they wrote, via examples of TensorFlow and PyTorch projects.

Process 91

Process Deep Learning Data Coding 91

KDnuggets

OCTOBER 8, 2019

To build an effective learning model, it is must to understand the quality issues exist in data & how to detect and deal with it. In general, data quality issues are categories in four major sets.

Data 73

Data Building Data Preparation IT 73

LinkedIn Engineering

DECEMBER 13, 2022

.�� The second component is the Ocelot pipelines, which are fully integrated data pipelines consisting of Java jobs, Spark jobs, and R jobs running on Azkaban (a LinkedIn open-source workflow manager), which both prepare modeling data according to the user configuration and executes causal modeling code.

Data Preparation 55

Data Preparation Data Science Designing Data Pipeline 55

AltexSoft

DECEMBER 15, 2021

Namely, AutoML takes care of routine operations within data preparation, feature extraction, model optimization during the training process, and model selection. In the meantime, we’ll focus on AutoML which drives a considerable part of the MLOps cycle, from data preparation to model validation and getting it ready for deployment.

Machine Learning 59

Machine Learning Deep Learning Algorithm Telecommunication 59