AltexSoft

NOVEMBER 15, 2022

First of all, this is an increase of around 5 percent over the summer of 2019: It’s already an indicator that things are going pretty well. A lot of quality data, to be even more exact. To learn the basics, you can read our dedicated article on how data is prepared for machine learning or watch a short video.

Hospitality 52

Hospitality Building Datasets Machine Learning 52

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. The team at Ritual started a free trial of Rockset and was impressed at the ease of use.

Food 40

Food Data Science SQL Data Warehouse 40

Rockset

APRIL 12, 2021

With a mission to digitize every aspect of construction materials logistics, the company launched CONNEX in 2019 to provide a SaaS application where suppliers, transportation providers and contractors on jobsites can collaborate on all the data collected by Command Alkon’s systems.

NoSQL 40

NoSQL Transportation Electronics Data Preparation 40

AltexSoft

MAY 12, 2021

Otherwise, let’s proceed to the first and most fundamental step in building AI-fueled computer vision tools — data preparation. Computer vision requires plenty of quality data, diverse in gender, race, and geography. The next large step in data preparation for computer vision is image labeling or annotation.

Medical 72

Medical Healthcare Datasets Machine Learning 72

U-Next

SEPTEMBER 22, 2022

Predictive Analytics is expected to generate more than six billion dollars in revenue by 2019. Many data warehouses are not directly connected to systems that store user data. A data science team may not be able to share data freely with some lines of business because they feel that their data belongs to them. .

Hospitality 40

Hospitality Algorithm Machine Learning Banking 40

AltexSoft

JULY 23, 2022

In October 2019, Microsoft reported artificial intelligence helped manufacturing companies outperform rivals stating that manufacturers adopting AI perform 12 percent better than their competitors.Therefore, we are likely to see the outburst of AI-based technologies in manufacturing along with the advent of new highly-paid workplaces in this area.

Manufacturing 52

Manufacturing Technology Machine Learning Transportation 52

Netflix Tech

OCTOBER 18, 2019

theme of the ML Platform meetup hosted at Netflix, Los Gatos on Sep 12, 2019. Their offline data preparation ETLs run on Spark and they use Airflow as the orchestration layer. Faisal Siddiqi Infrastructure for Contextual Bandits and Reinforcement Learning?—? they need to prevent malicious content from impacting the service.

Algorithm 51

Algorithm Architecture Machine Learning Deep Learning 51

AltexSoft

MAY 14, 2021

Talend is an open-source data integration and data management platform that empowers users with facilitated, self-service data preparation. Talend is considered one of the most effective and easy-to-use data integration tools focusing on Big Data. That’s a lot of data to learn from.

Big Data 78

Big Data Data Analytics IT NoSQL 78

Netflix Tech

OCTOBER 18, 2019

theme of the ML Platform meetup hosted at Netflix, Los Gatos on Sep 12, 2019. Their offline data preparation ETLs run on Spark and they use Airflow as the orchestration layer. Faisal Siddiqi Infrastructure for Contextual Bandits and Reinforcement Learning?—? they need to prevent malicious content from impacting the service.

Algorithm 40

Algorithm Architecture Machine Learning Deep Learning 40

ProjectPro

JANUARY 19, 2022

Data engineers will be in high demand as long as there is data to process. According to Dice Insights, data engineering was the top trending career in the technology industry in 2019, beating out computer scientists, web designers, and database architects. This real-world data engineering project has three steps.

Data Engineer 52

Data Engineer Data Engineering Engineering Data Storage 52

ProjectPro

MAY 18, 2016

from 2014-2019. A data scientist spends most of the time in data preparation so a HDaaS solution should offer a rich and powerful environment for analysis. 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

ProjectPro

JANUARY 15, 2021

Download OSIC Pulmonary Fibrosis Progression Dataset Data Science/Machine Learning Project Idea using OSIC Kaggle Dataset You can build a machine learning model to predict a patient’s severity of the decline in lung function. Each image is clinically rated on a scale of 0 to 4 based on the severity of diabetic retinopathy.

Machine Learning 40

Machine Learning Datasets Retail Banking 40

KDnuggets

DECEMBER 5, 2019

Increase your confidence to perform data cleaning with a broader perspective of what datasets typically look like, and follow this toolbox of code snipets to make your data cleaning process faster and more efficient.

Datasets 117

Datasets Data Coding Process 117

KDnuggets

NOVEMBER 12, 2019

While Pandas is the library for data processing in Python, it isn't really built for speed. Learn more about the new library, Modin, developed to distribute Pandas' computation to speedup your data prep.

Coding 119

Coding Python Data Process Process 119

KDnuggets

DECEMBER 10, 2019

From not sweating missing values, to determining feature importance for any estimator, to support for stacking, and a new plotting API, here are 5 new features of the latest release of Scikit-learn which deserve your attention.

Data Preparation 116

Data Preparation Machine Learning Python Data 116

KDnuggets

NOVEMBER 7, 2019

This post will walkthrough a Python implementation of a vocabulary class for storing processed text data and related metadata in a manner useful for subsequently performing NLP tasks.

Python 111

Python Metadata Process Data Preparation 111

KDnuggets

JULY 26, 2019

This article takes a closer look at the four fantastic things we should keep in mind when approaching every new data science project.

Data Science 115

Data Science Project Data Data Preparation 115

KDnuggets

NOVEMBER 7, 2019

In this tutorial, we show how to apply mathematical set operations (union, intersection, and difference) to Pandas DataFrames with the goal of easing the task of comparing the rows of two datasets.

Datasets 94

Datasets Data Preparation Data Science Python 94

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

DECEMBER 13, 2019

We show how to build intuitive and useful pipelines with Pandas DataFrame using a wonderful little library called pdpipe.

Building 110

Building Data Preparation Python Data 110

KDnuggets

OCTOBER 25, 2019

The pandas library offers core functionality when preparing your data using Python. But, many don't go beyond the basics, so learn about these lesser-known advanced methods that will make handling your data easier and cleaner.

Python 86

Python Data Preparation Data 86

KDnuggets

DECEMBER 4, 2019

Let’s say your project is humongous and needs data labeling to be done continuously - while you’re on-the-go, sleeping, or eating. I’m sure you’d appreciate User-generated Data Labeling. I’ve got 6 interesting examples to help you understand this, let’s dive right in!

Data 76

Data Project Data Preparation Data Science 76

KDnuggets

NOVEMBER 20, 2019

Your spectacularly-performing machine learning model could be subject to the common culprits of class imbalance and missing labels. Learn how to handle these challenges with techniques that remain open areas of new research for addressing real-world machine learning problems.

Machine Learning 79

Machine Learning Data Preparation Data 79

KDnuggets

SEPTEMBER 27, 2019

Data mapping is a way to organize various bits of data into a manageable and easy-to-understand system.

Machine Learning 89

Machine Learning Data Systems Management 89

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

KDnuggets

OCTOBER 31, 2019

AI-based models are highly dependent on accurate, clean, well-labeled, and prepared data in order to produce the desired output and cognition. These models are fed with bulky datasets covering an array of probabilities and computations to make its functioning as smart and gifted as human intelligence.

Datasets 55

Datasets Data Data Preparation IT 55

KDnuggets

JULY 31, 2019

Learn the essential skills needed to become a Data Science rockstar; Understand CNNs with Python + Tensorflow + Keras tutorial; Discover the best podcasts about AI, Analytics, Data Science; and find out where you can get the best Certificates in the field.

Data Science 45

Data Science Certification Python Data 45

KDnuggets

DECEMBER 16, 2019

The new technique allows the deployment of machine learning models that operate with minimum training data.

Machine Learning 55

Machine Learning Data Preparation Data 55

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