ODSC - Open Data Science

MAY 31, 2023

Be sure to check out his talk, “ Apache Kafka for Real-Time Machine Learning Without a Data Lake ,” there! The combination of data streaming and machine learning (ML) enables you to build one scalable, reliable, but also simple infrastructure for all machine learning tasks using the Apache Kafka ecosystem.

Data Lakes 131

Data Lakes Machine Learning Machine Learning Apache Kafka 131

Data Science Dojo

JULY 24, 2023

It supports various data processing operations, including batch processing, real-time stream processing, machine learning, and graph processing. Example Python code snippet using Apache Spark: Parallel Processing In distributed data processing, parallel processing is the key to efficient utilization of resources.

Big Data 195

Big Data Big Data Data Engineering Data Engineering 195

The MLOps Blog

FEBRUARY 5, 2023

In the later part of this article, we will discuss its importance and how we can use machine learning for streaming data analysis with the help of a hands-on example. Apache Spark : An open-source, distributed computing system that can handle big data processing tasks. What is streaming data? pip install tensorflow== 2.7.1 !

Machine Learning 72

Machine Learning Machine Learning Data Pipeline Apache Kafka 72

Pickl AI

JULY 20, 2023

Techniques like regression analysis, time series forecasting, and machine learning algorithms are used to predict customer behavior, sales trends, equipment failure, and more. Use machine learning algorithms to build a fraud detection model and identify potentially fraudulent transactions.

Analytics 40

Analytics Analytics Big Data Big Data 40

Pickl AI

DECEMBER 2, 2024

Internet of Things (IoT): Devices such as sensors, smart appliances, and wearables continuously collect and transmit data. Machine Learning Algorithms: These algorithms can identify patterns in data and make predictions based on historical trends.

Big Data 52

Big Data Big Data Data Lakes Apache Hadoop 52

Pickl AI

NOVEMBER 25, 2024

Internet of Things (IoT): Devices such as sensors, smart appliances, and wearables continuously collect and transmit data. Machine Learning Algorithms: These algorithms can identify patterns in data and make predictions based on historical trends.

Big Data 52

Big Data Big Data Data Lakes Apache Hadoop 52

Pickl AI

JULY 29, 2024

Machine Learning and Predictive Analytics Hadoop’s distributed processing capabilities make it ideal for training Machine Learning models and running predictive analytics algorithms on large datasets. Organisations that require low-latency data analysis may find Hadoop insufficient for their needs.

Hadoop 52

Hadoop Clustering Big Data Big Data 52