Data Science Dojo

FEBRUARY 20, 2023

Apache Spark Apache Spark is an in-memory distributed computing platform. It provides a large cluster of clusters on a single machine. Spark is a general-purpose distributed data processing engine that can handle large volumes of data for applications like data analysis, fraud detection, and machine learning.

Machine Learning 195

Machine Learning Machine Learning AWS Azure 195

Smart Data Collective

AUGUST 17, 2022

A hybrid cloud system is a cloud deployment model combining different cloud types, using both an on-premise hardware solution and a public cloud. It is because you usually see Kafka producers publish data or push it towards a Kafka topic so that the application can consume the data.

Apache Kafka 130

Apache Kafka ETL Data Lakes AWS 130

Applied Data Science

AUGUST 2, 2021

Automation Automating data pipelines and models ➡️ 6. First, let’s explore the key attributes of each role: The Data Scientist Data scientists have a wealth of practical expertise building AI systems for a range of applications. The Data Engineer Not everyone working on a data science project is a data scientist.

Data Science 130

Data Science Data Scientist ML ML 130

ODSC - Open Data Science

FEBRUARY 17, 2023

Computer science, math, statistics, programming, and software development are all skills required in NLP projects. Cloud Computing, APIs, and Data Engineering NLP experts don’t go straight into conducting sentiment analysis on their personal laptops.

Deep Learning 111

Deep Learning Deep Learning Data Science Natural Language Processing 111

phData

FEBRUARY 21, 2025

In this post, we will be particularly interested in the impact that cloud computing left on the modern data warehouse. We will explore the different options for data warehousing and how you can leverage this information to make the right decisions for your organization.

Data Warehouse 52

Data Warehouse Cloud Data ETL Cloud Computing 52

Data Science Dojo

JULY 3, 2024

Machine Learning : Supervised and unsupervised learning algorithms, including regression, classification, clustering, and deep learning. Big Data Technologies : Handling and processing large datasets using tools like Hadoop, Spark, and cloud platforms such as AWS and Google Cloud.

Data Science 150

Data Science Machine Learning Machine Learning Data Visualization 150

Dataconomy

FEBRUARY 23, 2023

This involves creating data validation rules, monitoring data quality, and implementing processes to correct any errors that are identified. Creating data pipelines and workflows Data engineers create data pipelines and workflows that enable data to be collected, processed, and analyzed efficiently.

Big Data 91

Big Data Big Data Data Engineer Data Engineering 91