DagsHub

APRIL 7, 2024

Image generated with Midjourney In today’s fast-paced world of data science, building impactful machine learning models relies on much more than selecting the best algorithm for the job. Data scientists and machine learning engineers need to collaborate to make sure that together with the model, they develop robust data pipelines.

Machine Learning 59

Machine Learning Machine Learning ML ML 59

DagsHub

JANUARY 14, 2025

In today's data-driven world, machine learning practitioners often face a critical yet underappreciated challenge: duplicate data management. 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.

Machine Learning 52

Machine Learning Machine Learning Clustering Algorithm 52

AWS Machine Learning Blog

OCTOBER 9, 2024

Amazon Lookout for Metrics is a fully managed service that uses machine learning (ML) to detect anomalies in virtually any time-series business or operational metrics—such as revenue performance, purchase transactions, and customer acquisition and retention rates—with no ML experience required. Choose Delete.

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ODSC - Open Data Science

JUNE 7, 2023

Bilokon | Visiting Lecturer, CEO and Founder | Imperial College London, Thalesians Ltd Apache Kafka for Real-Time Machine Learning Without a Data Lake: Kai Waehner | Global Field CTO, Author, International Speaker Semantic Analysis and Procedural Language Understanding in the Era of Large Language Models: Dr. Gözde Gül Şahin | Assistant Professor, (..)

Apache Kafka 52

Apache Kafka Machine Learning Machine Learning Data Science 52

AWS Machine Learning Blog

MARCH 30, 2023

To ensure real-time updates of ball recovery times, we have implemented Amazon Managed Streaming for Apache Kafka (Amazon MSK) as a central solution for data streaming and messaging. Additionally, the ball recovery times are sent to a specific topic in the MSK cluster, where they can be accessed by other Bundesliga Match Facts.

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AWS Machine Learning Machine Learning Apache Kafka 101

AWS Machine Learning Blog

NOVEMBER 3, 2023

m How it’s implemented In our quest to accurately determine shot speed during live matches, we’ve implemented a cutting-edge solution using Amazon Managed Streaming for Apache Kafka (Amazon MSK). Simultaneously, the shot speed data finds its way to a designated topic within our MSK cluster. km/h with a distance to goal of 20.61

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DagsHub

OCTOBER 23, 2024

Managing unstructured data is essential for the success of machine learning (ML) projects. Apache Kafka Apache Kafka is a distributed event streaming platform for real-time data pipelines and stream processing. Kafka is highly scalable and ideal for high-throughput and low-latency data pipeline applications.

Machine Learning 52

Machine Learning Machine Learning Data Lakes AI 52

ODSC - Open Data Science

JULY 22, 2023

We had bigger sessions on getting started with machine learning or SQL, up to advanced topics in NLP, and how to make deepfakes.

Apache Kafka 52

Apache Kafka Machine Learning Machine Learning Data Science 52

ODSC - Open Data Science

JULY 14, 2023

AI and Bias: How to Detect It and How to Prevent It Sandra Wachter, PhD | Professor, Technology and Regulation | Oxford Internet Institute, University of Oxford In recognition of the extensive biases and inequality that are present in training data, there has been much work done to test for bias in machine learning and AI systems.

Machine Learning 52

Machine Learning Machine Learning Apache Kafka Data Science 52

Pickl AI

AUGUST 9, 2024

Some of the most notable technologies include: Hadoop An open-source framework that allows for distributed storage and processing of large datasets across clusters of computers. Data Streaming Learning about real-time data collection methods using tools like Apache Kafka and Amazon Kinesis.

Big Data 52

Big Data Big Data Big Data Analytics Big Data Analytics 52

Dataconomy

FEBRUARY 23, 2023

Some of these solutions include: Distributed computing: Distributed computing systems, such as Hadoop and Spark, can help distribute the processing of data across multiple nodes in a cluster. This approach allows for faster and more efficient processing of large volumes of data.

Big Data 91

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Pickl AI

NOVEMBER 4, 2024

On the other hand, Data Science involves extracting insights and knowledge from data using Statistical Analysis, Machine Learning, and other techniques. Among these tools, Apache Hadoop, Apache Spark, and Apache Kafka stand out for their unique capabilities and widespread usage.

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52

Pickl AI

DECEMBER 2, 2024

Processing frameworks like Hadoop enable efficient data analysis across clusters. Apache Spark: A fast processing engine that supports both batch and real-time analytics, making it suitable for a wide range of applications. Key Takeaways Big Data originates from diverse sources, including IoT and social media. What is Big Data?

Big Data 52

Big Data Big Data Data Lakes Apache Hadoop 52

Pickl AI

NOVEMBER 25, 2024

Processing frameworks like Hadoop enable efficient data analysis across clusters. Apache Spark: A fast processing engine that supports both batch and real-time analytics, making it suitable for a wide range of applications. Key Takeaways Big Data originates from diverse sources, including IoT and social media. What is Big Data?

Big Data 52

Big Data Big Data Data Lakes Apache Hadoop 52

Mlearning.ai

MAY 16, 2023

The events can be published to a message broker such as Apache Kafka or Google Cloud Pub/Sub. The message broker can then distribute the events to various subscribers such as data processing pipelines, machine learning models, and real-time analytics dashboards.

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52

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

The MLOps Blog

MARCH 15, 2023

Typical examples include: Airbyte Talend Apache Kafka Apache Beam Apache Nifi While getting control over the process is an ideal position an organization wants to be in, the time and effort needed to build such systems are immense and frequently exceeds the license fee of a commercial offering. It connects to many DBs.

Data Pipeline 59

Data Pipeline ETL SQL Data Quality 59

ODSC - Open Data Science

MAY 24, 2023

Streaming Machine Learning Without a Data Lake The combination of data streaming and ML enables you to build one scalable, reliable, but also simple infrastructure for all machine learning tasks using the Apache Kafka ecosystem. Here’s why.

Data Lakes 52

Data Lakes ML ML Analytics 52

The MLOps Blog

AUGUST 11, 2023

Many questions regarding building machine learning pipelines and systems have already been answered and come from industry best practices and patterns. How should the machine learning pipeline operate? These stages are primarily considered in the domain of MLOps (machine learning operations).

ML 52

ML ML Machine Learning Machine Learning 52