Pickl AI

JULY 3, 2024

Introduction In the realm of databases, where information reigns supreme, attributes are the fundamental building blocks. They act as the defining characteristics of entities, providing the details that breathe life into our data. Each book on the shelf is an entity, a unique record with its own story.

Database 52

Database Data Analysis Data Analysis Data Wrangling 52

Flipboard

OCTOBER 25, 2023

Unstructured data is information that doesn’t conform to a predefined schema or isn’t organized according to a preset data model. Text, images, audio, and videos are common examples of unstructured data. Understanding the data, categorizing it, storing it, and extracting insights from it can be challenging.

AWS 166

AWS ML ML Analytics 166

ODSC - Open Data Science

JUNE 12, 2023

This article is an excerpt from the book Expert Data Modeling with Power BI, Third Edition by Soheil Bakhshi, a completely updated and revised edition of the bestselling guide to Power BI and data modeling. in an enterprise data warehouse. What is a Datamart? A replacement for datasets.

Power BI 52

Power BI Data Warehouse ETL Data Preparation 52

AWS Machine Learning Blog

MARCH 7, 2025

This new capability integrates the power of graph data modeling with advanced natural language processing (NLP). For Embeddings model , choose an embeddings model, such as Amazon Titan Text Embeddings v2. For Vector database , select Quick create a new vector store and then select Amazon Neptune Analytics (GraphRAG).

Analytics 122

Analytics Analytics AWS Natural Language Processing 122

Dataconomy

MAY 2, 2023

What do machine learning engineers do: They analyze data and select appropriate algorithms Programming skills To excel in machine learning, one must have proficiency in programming languages such as Python, R, Java, and C++, as well as knowledge of statistics, probability theory, linear algebra, and calculus.

ML 110

ML ML Machine Learning Machine Learning 110

O'Reilly Media

OCTOBER 19, 2021

We need robust versioning for data, models, code, and preferably even the internal state of applications—think Git on steroids to answer inevitable questions: What changed? Adapted from the book Effective Data Science Infrastructure. Data is at the core of any ML project, so data infrastructure is a foundational concern.

ML 145

ML ML Data Scientist AWS 145

Dataversity

MARCH 1, 2021

Data warehouse (DW) testers with data integration QA skills are in demand. Data warehouse disciplines and architectures are well established and often discussed in the press, books, and conferences. Each business often uses one or more data […].

Data Warehouse 52

Data Warehouse ETL Data Governance Data Quality 52

Flipboard

MARCH 23, 2023

It has helped to write a book. 2 However, you don’t need to know how Transformers work to use large language models effectively, any more than you need to know how a database works to use a database. At this point, it’s not clear how language models and their outputs fit into copyright law. What Is the Future?

AI 175

AI AI SQL Natural Language Processing 175

ODSC - Open Data Science

NOVEMBER 21, 2024

ODSC West 2024 is in the history books, and between the speakers, partners, and exhibitors, we have to say that it was our best one yet. Recapping ODSC West 2024: Our Biggest and Best One Yet! Here’s a rundown of what you missed. Forget the usual meetups — this one’s going to be pure energy and innovation!

Data Science 40

Data Science Database AI AI 40

phData

MARCH 11, 2024

A CDP has historically been an all-in-one platform designed to help companies collect, store, and unify customer data within a hosted database so that marketing and business teams can easily build audiences and activate data to downstream operational tools. dbt has become the standard for modeling.

Data Warehouse 52

Data Warehouse Cloud Data Data Models Data Modeling 52

Pickl AI

JULY 23, 2023

It is curated intentionally for a specific purpose, often to analyze and derive insights from the data it contains. Datasets are typically formatted and stored in files, databases, or spreadsheets, allowing for easy access and analysis. Types of Data 1. The post Data Demystified: What Exactly is Data?

Analytics 52

Analytics Analytics Predictive Analytics Data Analysis 52

Mlearning.ai

JUNE 8, 2023

Like traditional database index, vector index organizes the vectors into a data structure and makes it possible to navigate through the vectors and find the ones that are closest in terms of semantic similarity. USE uses a wide variety of data sets (exact details not provided), specifically target for generating sentence embeddings.

Machine Learning 52

Machine Learning Machine Learning Clustering Database 52

Dragan Djuric

MAY 13, 2021

def cart1 { :banana 10 :pineapple 7 :pears 3 } ) ( def cart2 { :pineapple 3 :mango 9 } ) Having defined product and cart data, we write a function that, given the products "database" and a cart, calculates the total price of the products in the cart. I've written two books where I go into much, much, more depth and width on this.

Algorithm 40

Algorithm Machine Learning Machine Learning Database 40

phData

SEPTEMBER 27, 2024

Introduction: The Customer Data Modeling Dilemma You know, that thing we’ve been doing for years, trying to capture the essence of our customers in neat little profile boxes? For years, we’ve been obsessed with creating these grand, top-down customer data models. Yeah, that one.

Data Models 52

Data Models Data Modeling Apache Kafka Data Lakes 52