O'Reilly on Data

NOVEMBER 19, 2024

A Latent Space Theory for Emergent Abilities in Large Language Models ” by Hui Jiang presents a statistical explanation for emergent LLM abilities, exploring a relationship between ambiguity in a language versus the scale of models and their training data. “ Do LLMs Really Adapt to Domains? that is required in your use case.

Unstructured Data 318

Unstructured Data Structured Data Statistics Modeling 318

David Menninger's Analyst Perspectives

SEPTEMBER 23, 2021

Sisu Data is an analytics platform for structured data that uses machine learning and statistical analysis to automatically monitor changes in data sets and surface explanations. It can prioritize facts based on their impact and provide a detailed, interpretable context to refine and support conclusions.

Key Performance Indicator 305

Key Performance Indicator Optimization Analytics Machine Learning 305

Analytics Vidhya

DECEMBER 25, 2020

ArticleVideos Image by Author In statistics, correlation or dependence is any statistical relationship, whether causal or not, between two random variables or bivariate data. The post Using Predictive Power Score to Pinpoint Non-linear Correlations appeared first on Analytics Vidhya.

Statistics 361

Statistics Analytics Structured Data Machine Learning 361

Analytics Vidhya

NOVEMBER 23, 2021

This article was published as a part of the Data Science Blogathon. Regression analysis is used to solve problems of prediction based on data statistical parameters. In this article, we will look at the use of a polynomial regression model on a simple example using real statistic data.

Modeling 400

Modeling Statistics Data Science Publishing 400

Analytics Vidhya

AUGUST 17, 2023

Introduction Pandas is more than just a name – it’s short for “panel data.” Use the Data formats with pandas in economics and statistics. It refers to structured data sets that hold observations across multiple periods for different entities or subjects. ” Now, what exactly does that mean?

Statistics 269

Statistics Structured Data Analytics IT 269

Analytics Vidhya

SEPTEMBER 9, 2021

This article was published as a part of the Data Science Blogathon What is Hypothesis Testing? Any data science project starts with exploring the data. When we perform an analysis on a sample through exploratory data analysis and inferential statistics we get information about the sample.

Machine Learning 372

Machine Learning Testing Statistics Data Science 372

Analytics Vidhya

JUNE 6, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon Introduction In applied Statistics and Machine Learning, Data Visualization is one. The post Must Known Data Visualization Techniques for Data Science appeared first on Analytics Vidhya.

Visualization 398

Visualization Data Science Statistics Machine Learning 398

Analytics Vidhya

MAY 31, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon Introduction The normal distribution is an important class of Statistical Distribution that. The post Normal Distribution : An Ultimate Guide appeared first on Analytics Vidhya.

Statistics 326

Statistics Data Science Publishing Analytics 326

David Menninger's Analyst Perspectives

SEPTEMBER 23, 2021

Sisu Data is an analytics platform for structured data that uses machine learning and statistical analysis to automatically monitor changes in data sets and surface explanations. It can prioritize facts based on their impact and provide a detailed, interpretable context to refine and support conclusions.

Machine Learning 235

Machine Learning Key Performance Indicator Optimization Analytics 235

CIO Business Intelligence

FEBRUARY 6, 2025

In life sciences, simple statistical software can analyze patient data. While this process is complex and data-intensive, it relies on structured data and established statistical methods. Use traditional tools for structured data and reserve LLMs for the truly complex stuff.

Unstructured Data 115

Unstructured Data Manufacturing Data Governance Sales 115

AWS Big Data

NOVEMBER 22, 2023

Today, we’re making available a new capability of AWS Glue Data Catalog that allows generating column-level statistics for AWS Glue tables. These statistics are now integrated with the cost-based optimizers (CBO) of Amazon Athena and Amazon Redshift Spectrum , resulting in improved query performance and potential cost savings.

Statistics 128

Statistics Data Lake Optimization Data-driven 128

AWS Big Data

OCTOBER 1, 2024

Amazon Redshift enables you to efficiently query and retrieve structured and semi-structured data from open format files in Amazon S3 data lake without having to load the data into Amazon Redshift tables. Amazon Redshift extends SQL capabilities to your data lake, enabling you to run analytical queries.

Data Lake 115

Data Lake Statistics Broadcasting Optimization 115

Analytics Vidhya

MAY 18, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon. Introduction Statistics is the foundation of Data Science. Before jumping to. The post Five Number Summary for Analysis! appeared first on Analytics Vidhya.

Statistics 271

Statistics Data Science Publishing Analytics 271

Analytics Vidhya

JUNE 11, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon Introduction Many engineers have never worked in statistics or data science. The post Know the basics of Exploratory Data Analysis appeared first on Analytics Vidhya.

Statistics 260

Statistics Data Science Publishing Analytics 260

Analytics Vidhya

JULY 8, 2023

But what does it take to clear the rigorous data science interview process?

Data Science 288

Data Science Statistics Machine Learning Analytics 288

Analytics Vidhya

JULY 25, 2022

Machine Learning is the method of teaching computer programs to do a specific task accurately (essentially a prediction) by training a predictive model using various statistical algorithms leveraging data. Introduction Let’s have a simple overview of what Machine Learning is. Source: [link] For […].

Machine Learning 271

Machine Learning Predictive Modeling Statistics Data Science 271

Analytics Vidhya

OCTOBER 28, 2020

This article was published as a part of the Data Science Blogathon. Introduction A popular and widely used statistical method for time series forecasting. The post How to Create an ARIMA Model for Time Series Forecasting in Python appeared first on Analytics Vidhya.

Forecasting 234

Forecasting Modeling Statistics Data Science 234

AWS Big Data

DECEMBER 17, 2024

We enhanced support for querying Apache Iceberg data and improved the performance of querying Iceberg up to threefold year-over-year. You can invoke these models using familiar SQL commands, making it simpler than ever to integrate generative AI capabilities into your data analytics workflows.

Data Lake 95

Data Lake Data Warehouse Data-driven Optimization 95

CIO Business Intelligence

MARCH 21, 2022

The data that data scientists analyze draws from many sources, including structured, unstructured, or semi-structured data. The more high-quality data available to data scientists, the more parameters they can include in a given model, and the more data they will have on hand for training their models.

Unstructured Data 137

Unstructured Data Data Analytics Analytics Data Science 137

CIO Business Intelligence

NOVEMBER 14, 2022

They emphasize access to and manipulation of large databases of structured data, often a time-series of internal company data and sometimes external data. Commonly used models include: Statistical models. XLSTAT is an Excel data analysis add-on geared for corporate users and researchers. Model-driven DSS.

Data mining 144

Data mining Data-driven Statistics OLAP 144

CIO Business Intelligence

JUNE 13, 2024

Using techniques from a range of disciplines, including computer programming, mathematics, and statistics, data analysts draw conclusions from data to describe, predict, and improve business performance. Data analyst role Data analysts mostly work with an organization’s structured data.

Data-driven 98

Data-driven Statistics Business Intelligence Data Collection 98

O'Reilly on Data

APRIL 19, 2021

We also asked what kinds of data our “mature” respondents are using. Most (83%) are using structured data (logfiles, time series data, geospatial data). form data). We’d expect most business applications to involve structured data, form data, or text data of some kind.

Enterprise 364

Enterprise Risk Modeling Manufacturing 364

Rocket-Powered Data Science

JULY 7, 2019

Computer Vision: Data Mining: Data Science: Application of scientific method to discovery from data (including Statistics, Machine Learning, data visualization, exploratory data analysis, experimentation, and more). NLG is a software process that transforms structured data into human-language content.

Internet of Things 157

Internet of Things Machine Learning Manufacturing IoT 157

datapine

MAY 27, 2020

An analytical report is a type of a business report that uses qualitative and quantitative company data to analyze as well as evaluate a business strategy or process while empowering employees to make data-driven decisions based on evidence and analytics. Patient Wait Time.

Reporting 245

Reporting Analytics Dashboards Sales 245

Domino Data Lab

AUGUST 9, 2021

Machine learning identifies patterns in data using algorithms that are primarily based on traditional methods of statistical learning. It’s most helpful in analyzing structured data. Based on the concept of neural networks, it’s useful for analyzing images, videos, text and other unstructured data.

Modeling 111

Modeling Deep Learning Machine Learning Statistics 111

AWS Big Data

OCTOBER 14, 2024

Amazon Athena provides interactive analytics service for analyzing the data in Amazon Simple Storage Service (Amazon S3). Amazon Redshift is used to analyze structured and semi-structured data across data warehouses, operational databases, and data lakes.

Metadata 102

Metadata Data Lake Modeling Data Warehouse 102

Analytics Vidhya

MARCH 19, 2020

Introduction Multicollinearity might be a handful to pronounce but it’s a topic you should be aware of in the machine learning field. The post What is Multicollinearity? Here’s Everything You Need to Know appeared first on Analytics Vidhya.

Machine Learning 397

Machine Learning Analytics IT Statistics 397

Rocket-Powered Data Science

JULY 19, 2023

I recently saw an informal online survey that asked users which types of data (tabular, text, images, or “other”) are being used in their organization’s analytics applications. This was not a scientific or statistically robust survey, so the results are not necessarily reliable, but they are interesting and provocative.

Data-driven 188

Data-driven Enterprise Analytics Machine Learning 188

Analytics Vidhya

SEPTEMBER 6, 2021

This article was published as a part of the Data Science Blogathon Introduction Q-Q plots are also known as Quantile-Quantile plots. As the name suggests, they plot the quantiles of a sample distribution against quantiles of a theoretical distribution.

Modeling 388

Modeling Data Science Publishing Analytics 388

CIO Business Intelligence

JUNE 28, 2022

For example, they may not be easy to apply or simple to comprehend but thanks to bench scientists and mathematicians alike, companies now have a range of logistical frameworks for analyzing data and coming to conclusions. More importantly, we also have statistical models that draw error bars that delineate the limits of our analysis.

Management 138

Management Internet of Things Statistics Data Science 138

AWS Big Data

FEBRUARY 26, 2025

AWS Glue Data catalog now automates generating statistics for new tables The AWS Glue Data Catalog now automates generating statistics for new tables. These statistics are integrated with a cost-based optimizer (CBO) from Amazon Redshift and Athena, resulting in improved query performance and potential cost savings.

Analytics 60

Analytics Data Lake Metadata Data Warehouse 60

Sisense

OCTOBER 6, 2020

Most commonly, we think of data as numbers that show information such as sales figures, marketing data, payroll totals, financial statistics, and other data that can be counted and measured objectively. This is quantitative data. It’s “hard,” structured data that answers questions such as “how many?”

Statistics 98

Statistics Unstructured Data Data-driven Visualization 98

Analytics Vidhya

OCTOBER 27, 2020

Overview A/B testing is a popular way to test your products and is gaining steam in the data science field Here, we’ll understand what. The post A/B Testing for Data Science using Python – A Must-Read Guide for Data Scientists appeared first on Analytics Vidhya.

Testing 400

Testing Data Science Analytics Structured Data 400

Rocket-Powered Data Science

JULY 14, 2023

I recently saw an informal online survey that asked users what types of data (tabular; text; images; or “other”) are being used in their organization’s analytics applications. This was not a scientific or statistically robust survey, so the results are not necessarily reliable, but they are interesting and provocative.

Analytics 166

Analytics Internet of Things Data Science Prescriptive Analytics 166

Analytics Vidhya

MAY 19, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon Introduction In my previous article, I talk about the theoretical concepts. The post Feature Engineering – How to Detect and Remove Outliers (with Python Code) appeared first on Analytics Vidhya.

Data Science 364

Data Science Publishing Analytics Statistics 364

Analytics Vidhya

APRIL 25, 2020

Overview Microsoft Excel is one of the most widely used tools for data analysis Learn the essential Excel functions used to analyze data for. The post 10+ Simple Yet Powerful Excel Tricks for Data Analysis appeared first on Analytics Vidhya.

Analytics 391

Analytics Structured Data Data Processing Statistics 391

Analytics Vidhya

FEBRUARY 17, 2021

ArticleVideos This article was published as a part of the Data Science Blogathon. What is Multicollinearity? One of the key assumptions for a regression-based. The post Multicollinearity: Problem, Detection and Solution appeared first on Analytics Vidhya.

Data Science 389

Data Science Publishing Analytics Structured Data 389