Pickl AI

NOVEMBER 4, 2024

Summary: The fundamentals of Data Engineering encompass essential practices like data modelling, warehousing, pipelines, and integration. Understanding these concepts enables professionals to build robust systems that facilitate effective data management and insightful analysis. What is Data Engineering?

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

Women in Big Data

OCTOBER 9, 2024

Refer to Unlocking the Power of Big Data Article to understand the use case of these data collected from various sources. Data Ingestion: Data is collected and funneled into the pipeline using batch or real-time methods, leveraging tools like Apache Kafka, AWS Kinesis, or custom ETL scripts.

Big Data 59

Big Data Big Data Apache Kafka Data Pipeline 59

Mlearning.ai

MAY 16, 2023

Data engineering is a rapidly growing field that designs and develops systems that process and manage large amounts of data. There are various architectural design patterns in data engineering that are used to solve different data-related problems. BECOME a WRITER at MLearning.ai.

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52

The MLOps Blog

FEBRUARY 5, 2023

There are many platforms and sources that generate this kind of data. In this article, we will go through the basics of streaming data, what it is, and how it differs from traditional data. We will also get familiar with tools that can help record this data and further analyse it.

Machine Learning 72

Machine Learning Machine Learning Data Pipeline Apache Kafka 72

DagsHub

OCTOBER 23, 2024

Managing unstructured data is essential for the success of machine learning (ML) projects. Without structure, data is difficult to analyze and extracting meaningful insights and patterns is challenging. This article will discuss managing unstructured data for AI and ML projects. How to properly manage unstructured data.

Machine Learning 52

Machine Learning Machine Learning Data Lakes AI 52

DagsHub

JANUARY 14, 2025

This article is an attempt to delve into how duplicate data can affect machine learning models, and how it impacts their accuracy and other performance metrics. We'll try to uncover practical strategies to identify, analyze, and manage duplicate data effectively. We hope you find this article thought-provoking!

Machine Learning 52

Machine Learning Machine Learning Clustering Algorithm 52

The MLOps Blog

AUGUST 11, 2023

1 Data Ingestion (e.g., Apache Kafka, Amazon Kinesis) 2 Data Preprocessing (e.g., pandas, NumPy) 3 Feature Engineering and Selection (e.g., 1 Data Ingestion (e.g., Apache Kafka, Amazon Kinesis) 2 Data Preprocessing (e.g., pandas, NumPy) 3 Feature Engineering and Selection (e.g.,

ML 52

ML ML Machine Learning Machine Learning 52