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

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

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. What is Natural Language Processing? Natural language processing or NLP is a branch of Artificial Intelligence that gives machines the ability to understand natural human speech.

Process 139

Process Deep Learning Datasets Machine Learning 139

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

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

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

Confessions of a Data Guy

APRIL 19, 2024

The idea was to see if the two tools could process “larger than memory” datasets with lazy execution. Back in March, I did a writeup and experiment called DuckDB vs Polars, Thunderdom, 16GB on 4GB machine challenge. Polars worked fine, DuckDB failed in spectacular fashion.

IT 140

IT Datasets Process Data 140

Analytics Vidhya

FEBRUARY 23, 2023

Introduction Big Data is a large and complex dataset generated by various sources and grows exponentially. It is so extensive and diverse that traditional data processing methods cannot handle it. The volume, velocity, and variety of Big Data can make it difficult to process and analyze.

Big Data Tools 234

Big Data Tools Big Data Datasets Data 234

phData: Data Engineering

SEPTEMBER 19, 2023

However, to fully harness the potential of a data lake, effective data modeling methodologies and processes are crucial. With many data modeling methodologies and processes available, choosing the right approach can be daunting. Efficiency through being able to streamline data storage and retrieval processes.

Data Lake 52

Data Lake Process Metadata Data Warehouse 52

Knowledge Hut

MAY 3, 2024

Machine Learning Process: The process of Machine Learning can be broken down into several parts, most of which is based around “Data” The following steps show the Machine Learning Process. Hence, the removal or processing of irregularities is necessary to promote data homogeneity.

Machine Learning 52

Machine Learning Datasets Algorithm Architecture 52

Christophe Blefari

APRIL 19, 2024

It was trained on a large dataset containing 15T tokens (compared to 2T for Llama 2). This is super interesting because it details important steps of the generative process. In a nutshell it says: Llama is available in 8B and 70B, 400B is coming once training will be completed—and approaching GPT-4 performances.

MySQL 130

MySQL Data Datasets SQL 130

Databand.ai

JULY 19, 2023

Complete Guide to Data Ingestion: Types, Process, and Best Practices Helen Soloveichik July 19, 2023 What Is Data Ingestion? Data Ingestion is the process of obtaining, importing, and processing data for later use or storage in a database. However, the ultimate goal is simple: to prepare data for immediate use.

Data Ingestion 52

Data Ingestion Process Data Cleanse Data Governance 52

Knowledge Hut

APRIL 25, 2024

Recognizing the difference between big data and machine learning is crucial since big data involves managing and processing extensive datasets, while machine learning revolves around creating algorithms and models to extract valuable information and make data-driven predictions.

Machine Learning 52

Machine Learning Big Data Unstructured Data Data Mining 52

Knowledge Hut

FEBRUARY 29, 2024

Learning Data Analysis in Excel Data analysis is a process of inspecting, cleaning, transforming and modelling data with an objective of uncover the useful knowledge, results and supporting decision. Then, based on this information from the sample, defect or abnormality the rate for whole dataset is considered.

Data Science 98

Data Science Datasets Database Design Machine Learning 98

Analytics Vidhya

FEBRUARY 6, 2023

Introduction HDFS (Hadoop Distributed File System) is not a traditional database but a distributed file system designed to store and process big data. It is a core component of the Apache Hadoop ecosystem and allows for storing and processing large datasets across multiple commodity servers.

Data Storage 185

Data Storage Big Data Hadoop Datasets 185

Knowledge Hut

APRIL 23, 2024

It involves processing and analyzing massive datasets that cannot be managed with traditional data processing techniques. It involves working with datasets that can be managed using standard hardware and software without the need for complex infrastructure. Small Data is collected and processed at a slower pace.

Big Data 52

Big Data Datasets Data Analysis Media 52

Knowledge Hut

APRIL 23, 2024

Data Types Big Data Data Mining Big data refers to robust and complicated datasets that require a high level of expertise and tools for managing, processing, or analyzing. Traditional data processing techniques cannot be used. Data mining is capable of handling comparatively smaller datasets.

Data Mining 52

Data Mining Big Data Database-centric Unstructured Data 52

Knowledge Hut

MAY 3, 2024

Variance : This is what happens when a machine learning model performs well with the training dataset but poorly with the test dataset. Generalizing a model to new datasets allows us to use machine learning algorithms to make predictions and classify data daily. The size of the training dataset used is not enough.

Machine Learning 52

Machine Learning Datasets Algorithm Data Science 52

Knowledge Hut

FEBRUARY 1, 2024

Movie Recommendation System Architecture The movie recommendation system architecture is a complex process that utilizes various algorithms to suggest movies to users based on their preferences. Suppose we have a dataset of user ratings for various movies, where each row represents a user & each column represents a movie.

Systems 98

Systems Entertainment Datasets Algorithm 98

Knowledge Hut

APRIL 23, 2024

With the help of big data analytics, we can gain insights from large datasets and reveal previously concealed patterns, trends, and correlations. Big data refers to large volumes of data or datasets that cannot be gleaned or parsed with traditional tools and methods. Big data has revolutionized the world of data science altogether.

Big Data 52

Big Data Media Datasets Unstructured Data 52

Monte Carlo

APRIL 12, 2022

Data teams love the idea of automating data engineering processes in principle. In this spirit, we got together to brainstorm nine data engineering processes we believe are ripe for automation. For these data engineering processes, there is no need to be a code warrior. We’ve felt it ourselves.

Data Engineering 52

Data Engineering Data Engineer Process Engineering 52

Towards Data Science

AUGUST 29, 2023

Today, we will delve into the intricacies the problem of missing data , discover the different types of missing data we may find in the wild, and explore how we can identify and mark missing values in real-world datasets. Image by Author. Let’s consider an example. Image by Author. Image by Author.

Datasets 109

Datasets Machine Learning Data Data Science 109

Confluent

FEBRUARY 21, 2019

By taking data from a tool such as Sysmon and streaming it into Kafka for processing in KSQL, you can rapidly detect suspicious behavior by looking for a process spawning a new process that makes an external network connection. This is because the Create method allows a user to create a process either locally or remotely.

Process 81

Process Kafka Datasets SQL 81

U-Next

OCTOBER 16, 2022

The KDD process in data mining is used in business in the following ways to make better managerial decisions: . This article will briefly discuss the KDD process in data mining and the KDD process steps. . KDD relies heavily on data mining knowledge management , which is the foundation of the entire process. .

Data Mining 40

Data Mining Process IT Raw Data 40

ThoughtSpot

MARCH 5, 2024

These tables provide a centralized location to host both your raw data and transformed datasets optimized for AI-powered analytics with ThoughtSpot. The refresh process automatically computes changes in the source data and merges those updates into the dynamic table.

BI 94

BI Datasets Raw Data SQL 94

ArcGIS

JANUARY 2, 2024

Process Landsat and GEDI datasets in the cloud and predict aboveground biomass for the state of Oregon using machine learning in ArcGIS Pro.

Cloud 109

Cloud Datasets Machine Learning Data 109

Knowledge Hut

APRIL 23, 2024

While both deal with large datasets, but when it comes to data warehouse vs big data, they have different focuses and offer distinct advantages. The key characteristics of big data are commonly described as the three V's: volume (large datasets), velocity (high-speed data ingestion), and variety (data in different formats).

Data Warehouse 52

Data Warehouse Big Data Unstructured Data Hadoop 52

Knowledge Hut

JULY 28, 2023

Machine learning offers scalability and efficiency, processing large datasets quickly. A dataset's anomalies may provide valuable information about inconsistencies, mistakes, fraud, or unusual events. By taking into account the statistical characteristics of the entire dataset, global outliers are frequently found.

Machine Learning 98

Machine Learning Algorithm Datasets Healthcare 98

Knowledge Hut

APRIL 25, 2024

In the past, this data was too large and complex for traditional data processing tools to handle. However, advances in technology have now made it possible to store, process, and analyze big data quickly and effectively. Data capture refers to the process of collecting data from a variety of sources.

Big Data 98

Big Data Technology NoSQL Hadoop 98

Knowledge Hut

NOVEMBER 28, 2023

Whether you are working on a personal project, learning the concepts, or working with datasets for your company, the primary focus is a data acquisition and data understanding. In this article, we will look at 31 different places to find free datasets for data science projects. What is a Data Science Dataset?

Datasets 96

Datasets Data Science Project Banking 96

Knowledge Hut

JANUARY 3, 2024

Data visualization is the process of understanding the data in a more detailed way, using graphical representations such as graphs and plots. The packages include Pandas for processing, Matplotib for visualization, seaborn for advanced visuals, and Numpy for calculations. In today’s age, a lot of data is being generated daily.

Python 98

Python Programming Language Datasets R (Programming) 98

Monte Carlo

APRIL 1, 2024

Because effective data cleaning best practices fix and remove incorrect, inaccurate, corrupted, duplicate, or incomplete data in your dataset; data cleaning removes the garbage before it enters your pipelines. Continuously Monitor and Refine Processes Elevate Data Cleaning Best Practices with Monte Carlo 1.

High Quality Data 52

High Quality Data Datasets Data Data Pipeline 52

Netflix Tech

NOVEMBER 13, 2023

In this blog post, we will introduce speech and music detection as an enabling technology for a variety of audio applications in Film & TV, as well as introduce our speech and music activity detection (SMAD) system which we recently published as a journal article in EURASIP Journal on Audio, Speech, and Music Processing.

Datasets 89

Datasets Metadata Algorithm Architecture 89

RandomTrees

APRIL 12, 2024

This iterative process ensures that the model remains aligned with the evolving patterns and dynamics present in the underlying data. Incorporate New Data By refreshing the training dataset through retraining, machine learning models gain exposure to the latest examples and patterns present in the data. What is Model Retraining?

Machine Learning 52

Machine Learning Datasets Systems Process 52

Databand.ai

MAY 30, 2023

Data quality can be influenced by various factors, such as data collection methods, data entry processes, data storage, and data integration. Improved data quality leads to reduced errors in these processes and increases productivity. A complete dataset allows for more comprehensive analysis and decision-making.

Data Cleanse 85

Data Cleanse Datasets Data Governance Data Validation 85

Hevo

APRIL 4, 2024

Data reconciliation is a process where datasets are compared and matched to ensure accuracy and consistency. The process involves identifying discrepancies in the data and resolving them proactively to prevent an impact on the outcomes. Data reconciliation is essential for financial accuracy, but it can be tedious.

Banking 52

Banking Datasets Data Process 52