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.

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Machine Learning Machine Learning ML ML 59

Women in Big Data

OCTOBER 9, 2024

These procedures are central to effective data management and crucial for deploying machine learning models and making data-driven decisions. After this, the data is analyzed, business logic is applied, and it is processed for further analytical tasks like visualization or machine learning. What is a Data Pipeline?

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Big Data Big Data Apache Kafka Data Pipeline 59

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.

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Big Data Big Data Data Engineering Data Engineering 195

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.

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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.

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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. It also provides the foundation for downstream machine learning or AI applications.

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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. His skills and areas of expertise include application development, data science, machine learning, and big data.

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Data Science Blog

JUNE 27, 2023

In practical implementation, the Kappa architecture is commonly deployed using Apache Kafka or Kafka-based tools. Applications can directly read from and write to Kafka or an alternative message queue tool. This architectural concept relies on event streaming as the core element of data delivery.

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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, (..)

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IBM Journey to AI blog

NOVEMBER 29, 2023

Aggregates as predictive insights : Aggregates, which consolidate data from various sources across your business environment, can serve as valuable predictors for machine learning (ML) algorithms. Event processing helps continuously update and refine our understanding of ongoing business scenarios.

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Artificial Intelligence Artificial Intelligence Apache Kafka AI 105

Precisely

DECEMBER 28, 2023

One very popular platform is Apache Kafka , a powerful open-source tool used by thousands of companies. But in all likelihood, Kafka doesn’t natively connect with the applications that contain your data. Interested in learning more about streaming data pipelines for your organization? You need a separate tool to do that.

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Data Pipeline Apache Kafka Big Data Big Data 91

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.

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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). His skills and areas of expertise include application development, data science, and machine learning (ML).

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AWS Apache Kafka Data Scientist Data Science 119

AWS Machine Learning Blog

APRIL 19, 2023

Businesses are increasingly using machine learning (ML) to make near-real-time decisions, such as placing an ad, assigning a driver, recommending a product, or even dynamically pricing products and services. Apache Flink is a popular framework and engine for processing data streams.

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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

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.

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AWS Machine Learning Blog

SEPTEMBER 11, 2024

In this post, we demonstrate how to build a robust real-time anomaly detection solution for streaming time series data using Amazon Managed Service for Apache Flink and other AWS managed services. This solution employs machine learning (ML) for anomaly detection, and doesn’t require users to have prior AI expertise.

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ODSC - Open Data Science

JUNE 1, 2023

We’re going to assume that the pizza service already captures orders in Apache Kafka and is also keeping a record of its customers and the products that they sell in MySQL. Apache Pinot is a real-time OLAP database built at LinkedIn to deliver scalable real-time analytics with low latency.

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Analytics Analytics Apache Kafka Data Science 98

AWS Machine Learning Blog

JANUARY 6, 2023

The key requirement for TR’s new machine learning (ML)-based personalization engine was centered around an accurate recommendation system that takes into account recent customer trends. Then the events are ingested into TR’s centralized streaming platform, which is built on top of Amazon Managed Streaming for Kafka (Amazon MSK).

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ODSC - Open Data Science

FEBRUARY 6, 2024

Apache Kafka For data engineers dealing with real-time data, Apache Kafka is a game-changer. REGISTER NOW Data Orchestration and Workflow Management Apache Airflow Apache Airflow is renowned for its ability to build and schedule complex data pipelines.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

AWS Machine Learning Blog

OCTOBER 9, 2024

I am currently using Apache Kafka. Learn more about this feature in the AWS Machine Learning blog. She is currently focused on machine learning and AI technologies. The #customerwork Slack channel is being used to communicate about an upcoming customer engagement, as shown in the following figure.

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Pickl AI

DECEMBER 4, 2024

Summary: The future of Data Science is shaped by emerging trends such as advanced AI and Machine Learning, augmented analytics, and automated processes. Continuous learning and adaptation will be essential for data professionals. Automated Machine Learning (AutoML) will democratize access to Data Science tools and techniques.

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Data Science Data Scientist Machine Learning Machine Learning 52

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 !

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Machine Learning Machine Learning Data Pipeline Apache Kafka 72

Alation

AUGUST 4, 2022

Big data got“ more leaders and people in the organization to use data, analytics, and machine learning in their decision making,” says former CIO Isaac Sacolick. Spark, Tensorflow, Apache Kafka, et cetera, are all out found in cloud databases,” points out Jones. Blindspots and silos left vital gaps empty.

Big Data 95

Big Data Big Data Apache Kafka Data Lakes 95

Pickl AI

SEPTEMBER 18, 2024

Read More: How Airbnb Uses Big Data and Machine Learning to Offer World-Class Service Netflix’s Big Data Infrastructure Netflix’s data infrastructure is one of the most sophisticated globally, built primarily on cloud technology. Data at Rest This includes storage solutions such as S3 Data Warehouse and Cassandra.

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Big Data Big Data Apache Kafka Big Data Analytics 52

Pickl AI

AUGUST 9, 2024

Data Streaming Learning about real-time data collection methods using tools like Apache Kafka and Amazon Kinesis. Machine Learning Algorithms Basic understanding of Machine Learning concepts and algorithm s, including supervised and unsupervised learning techniques.

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ODSC - Open Data Science

OCTOBER 9, 2024

These tools use machine learning models trained on vast amounts of code to assist developers in writing cleaner, more efficient code. Tools like Testim and Applitools leverage machine learning to improve both unit testing and UI testing. How you might ask?

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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

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Dataconomy

FEBRUARY 23, 2023

Some of these solutions include: Stream processing: Stream processing systems, such as Apache Kafka and Apache Flink, can help process high-speed data streams in real-time. Solutions for managing and processing high velocity data Data engineers can use various solutions to manage and process high-speed data streams.

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Big Data Big Data Data Engineering Data Engineer 91

Pickl AI

JULY 25, 2024

Enhanced Data Utilisation Effective ingestion unlocks the full potential of data by making it available for advanced analytics, machine learning, and artificial intelligence applications, driving innovation and business growth. Apache Kafka An open-source platform designed for real-time data streaming.

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Apache Kafka Data Lakes Data Warehouse Data Quality 52

Pickl AI

OCTOBER 21, 2024

In response, Twitter has implemented various solutions, including Apache Kafka, a distributed streaming platform that helps manage the data flow from user interactions. Using Kafka, Twitter can effectively handle high-throughput data streams, enabling users to receive timely notifications and updates.

Database 52

Database Apache Kafka Machine Learning Machine Learning 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

Pickl AI

DECEMBER 2, 2024

Machine Learning Algorithms: These algorithms can identify patterns in data and make predictions based on historical trends. Analytics Tools Once data is stored and processed, analytics tools help organisations extract valuable insights.Analytics tools play a critical role in transforming raw data into actionable insights.

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.

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Pickl AI

NOVEMBER 25, 2024

Machine Learning Algorithms: These algorithms can identify patterns in data and make predictions based on historical trends. Analytics Tools Once data is stored and processed, analytics tools help organisations extract valuable insights.Analytics tools play a critical role in transforming raw data into actionable insights.

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

Mlearning.ai

AUGUST 4, 2023

Apache Kafka and R abbitMQ are particularly popular in LEs. Graph 7: Percentage of Programming Languages MiscTech Tools In Both LEs and SMEs: ‘. NET (5+) ’, ‘ pandas ’, ‘ numpy ’, and ‘. NET Framework (1.0–4.8)’ 4.8)’ are widely used.

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