Dataconomy

APRIL 18, 2023

Examples of parallel processing in daily life Parallel processing is used in many everyday applications, from simple tasks such as downloading files and browsing the web to more complex operations such as image and video processing. This can lead to more accurate insights and better decision-making.

Big Data Analytics 103

Big Data Analytics Big Data Analytics Machine Learning Machine Learning 103

Smart Data Collective

SEPTEMBER 2, 2021

Its reliable build-in video downloader can be helpful for users to download videos from YouTube, Vimeo, TikTok, and 1000+ online sites. With big data, VideoProc Converter is competent to provide video producers these useful features that were not possible before. Everyone has something to gain from data analysis.

Big Data 132

Big Data Big Data Data Analysis Data Analysis 132

Smart Data Collective

JUNE 30, 2022

Geoffrey Moore tweeted about this in 2012 when he said: “Without big data analytics, companies are blind and deaf, wandering out onto the Web like deer on a freeway.”. His statement about the importance of big data in social media marketing is even more true today. Explaining How Instagram Stories Work.

Big Data 132

Big Data Big Data Analytics Analytics 132

AWS Machine Learning Blog

OCTOBER 5, 2023

First, download the Llama 2 model and training datasets and preprocess them using the Llama 2 tokenizer. For detailed guidance of downloading models and the argument of the preprocessing script, refer to Download LlamaV2 dataset and tokenizer. Next, compile the model: sbatch --nodes 4 compile.slurm./llama_7b.sh

AWS 122

AWS Machine Learning Machine Learning Deep Learning 122

ODSC - Open Data Science

OCTOBER 17, 2023

We’ve created synthetic data that closely resembles the metrics collected from a production pod with some of our customers. You can download our synthetic data from here. Her interests lie in software testing, cloud computing, big data analytics, systems engineering, and architecture.

Data Science 98

Data Science Computer Science Computer Science Database 98

AWS Machine Learning Blog

MAY 10, 2023

In this post, we show how you can publish predictive dashboards in QuickSight using ML-based predictions from Canvas, without explicitly downloading predictions and importing into QuickSight. You can copy the prediction by choosing Copy , or download it by choosing Download prediction.

ML 92

ML ML AWS Data Analysis 92

AWS Machine Learning Blog

NOVEMBER 29, 2023

You can import data directly through over 50 data connectors such as Amazon Simple Storage Service (Amazon S3), Amazon Athena , Amazon Redshift , Snowflake, and Salesforce. In this walkthrough, we will cover importing your data directly from Snowflake. You can download the dataset loans-part-1.csv csv and loans-part-2.csv.

Data Preparation 123

Data Preparation ML ML Data Quality 123

AWS Machine Learning Blog

JUNE 3, 2024

You can import data from multiple sources, ranging from AWS services, such as Amazon Simple Storage Service (Amazon S3) and Amazon Redshift, to third-party or partner services, including Snowflake or Databricks. To learn more about importing data to SageMaker Canvas, see Import data into Canvas. Choose Generate predictions.

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Flipboard

MARCH 22, 2023

Snowflake is a cloud data platform that provides data solutions for data warehousing to data science. Snowflake is an AWS Partner with multiple AWS accreditations, including AWS competencies in machine learning (ML), retail, and data and analytics. You can either download the report or view it online.

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AWS Data Preparation Azure Data Scientist 123

Precisely

AUGUST 8, 2023

The Need for Data Governance The number of connected devices has expanded rapidly in recent years, as mobile phones, telematics devices, IoT sensors, and more have gained widespread adoption. At the same time, big data analytics has come of age. The post 5 Data Governance Best Practices appeared first on Precisely.

Data Governance 52

Data Governance Data Quality Big Data Analytics Big Data Analytics 52

Pickl AI

JULY 29, 2024

It utilises the Hadoop Distributed File System (HDFS) and MapReduce for efficient data management, enabling organisations to perform big data analytics and gain valuable insights from their data. Download and extract the Apache Hadoop distribution on all nodes.

Hadoop 52

Hadoop Clustering Big Data Big Data 52

Pickl AI

MARCH 11, 2025

Key Takeaways Big Data analyses large datasets to uncover trends, patterns, and insights for informed decision-making. Cloud Computing provides scalable infrastructure for data storage, processing, and management. Both technologies complement each other by enabling real-time analytics and efficient data handling.

Cloud Computing 52

Cloud Computing Big Data Big Data Big Data Analytics 52

Flipboard

MARCH 7, 2023

Each user role such as a data scientist; an ML, MLOps, or DevOps engineer; and an administrator can choose the most suitable approach based on their needs, place in the development cycle, and enterprise guardrails. He develops and codes cloud native solutions with a focus on big data, analytics, and data engineering.

Python 123

Python AWS ML ML 123

Mlearning.ai

JANUARY 26, 2023

Most important to note about ARCO is that, unlike data systems from a decade ago, modern data cubes should ideally be Cloud-native (meaning: ready for fast and efficient web-services / scalable applications / API’s) and pre-processed so that they can be directly used for modelling and eventually for decision-making.

AWS 98

AWS Database Data Science Clean Data 98

Smart Data Collective

MARCH 7, 2021

Analytics is playing an increasingly important role in the future of the music industry. A growing number of music companies are discovering new applications for analytics tools, which can streamline many important aspects of their industry. The Past, Present and Future of Analytics in the Music Industry. Download cards?

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Analytics Analytics Big Data Big Data 129