Analytics Vidhya

JUNE 27, 2020

Overview There are a plethora of data science tools out there – which one should you pick up? The post 22 Widely Used Data Science and Machine Learning Tools in 2020 appeared first on Analytics Vidhya. Here’s a list of over 20.

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Analytics Vidhya

SEPTEMBER 22, 2022

This article was published as a part of the Data Science Blogathon. Dale Carnegie” Apache Kafka is a Software Framework for storing, reading, and analyzing streaming data. Introduction “Learning is an active process. We learn by doing. Only knowledge that is used sticks in your mind.-

Data Pipeline 270

Data Pipeline Apache Kafka Internet of Things Data Science 270

Dataconomy

MAY 26, 2017

Data processing today is done in form of pipelines which include various steps like aggregation, sanitization, filtering and finally generating insights by applying various statistical models. Amazon Kinesis is a platform to build pipelines for streaming data at the scale of terabytes per hour. Parts of the Kinesis platform are.

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Apache Kafka Data Analysis Big Data Big Data 155

Data Science Dojo

MARCH 9, 2023

Data Science Dojo is offering Memphis broker for FREE on Azure Marketplace preconfigured with Memphis, a platform that provides a P2P architecture, scalability, storage tiering, fault-tolerance, and security to provide real-time processing for modern applications suitable for large volumes of data. Are you already feeling tired?

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IBM Journey to AI blog

NOVEMBER 3, 2023

It allows your business to ingest continuous data streams as they happen and bring them to the forefront for analysis, enabling you to keep up with constant changes. Apache Kafka boasts many strong capabilities, such as delivering a high throughput and maintaining a high fault tolerance in the case of application failure.

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Apache Kafka Data Warehouse Data Pipeline Big Data 79

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.

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Data Lakes Machine Learning Machine Learning Apache Kafka 131

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. As industries increasingly rely on data-driven insights, ethical considerations regarding data privacy and bias mitigation will become paramount.

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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. He tweets at @markhneedham.

Analytics 98

Analytics Analytics Apache Kafka Data Science 98

Data Science Blog

JUNE 27, 2023

This architectural concept relies on event streaming as the core element of data delivery. 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.

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Big Data Big Data Apache Kafka Database 130

Data Science Dojo

JULY 24, 2023

Internet of Things (IoT) Data Processing: Stream processing is vital for handling continuous data streams from IoT devices, enabling real-time monitoring and control.

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Big Data Big Data Data Engineering Data Engineering 195

ODSC - Open Data Science

FEBRUARY 6, 2024

Spark offers a versatile range of functionalities, from batch processing to stream processing, making it a comprehensive solution for complex data challenges. Apache Kafka For data engineers dealing with real-time data, Apache Kafka is a game-changer.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

ODSC - Open Data Science

JUNE 7, 2023

ODSC Europe is next week, coming up June 14th-15th, and we can’t wait to bring the data science community together, both in-person and virtually, to reconnect, learn, and grow. Our in-person passes are almost sold out, but don’t worry.

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ODSC - Open Data Science

JULY 22, 2023

The week was filled with engaging sessions on top topics in data science, innovation in AI, and smiling faces that we haven’t seen in a while. Expo Hall ODSC events are more than just data science training and networking events. We’re a few weeks removed from ODSC Europe 2023 and we couldn’t have left on a better note.

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Apache Kafka Machine Learning Machine Learning Data Science 52

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. Register for free!

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Data Lakes ML ML Analytics 52

ODSC - Open Data Science

JULY 14, 2023

Time Series Forecasting for Managers — All Forecasts Are Wrong but Some Are Useful Tanvir Ahmed Shaikh | Data Strategist (Director) | Genentech, Inc Time series forecasting remains an under-appreciated technique in data science education, often overshadowed by more popular machine learning methods.

Machine Learning 52

Machine Learning Machine Learning Apache Kafka Data Science 52

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

Streaming ingestion – An Amazon Kinesis Data Analytics for Apache Flink application backed by Apache Kafka topics in Amazon Managed Streaming for Apache Kafka (MSK) (Amazon MSK) calculates aggregated features from a transaction stream, and an AWS Lambda function updates the online feature store.

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AWS Machine Learning Blog

MARCH 30, 2023

How it’s implemented Positional data from an ongoing match, which is recorded at a sampling rate of 25 Hz, is utilized to determine the time taken to recover the ball. This allows for seamless communication of positional data and various outputs of Bundesliga Match Facts between containers in real time.

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AWS Machine Learning Machine Learning Apache Kafka 93

Alation

AUGUST 4, 2022

Spark, Tensorflow, Apache Kafka, et cetera, are all out found in cloud databases,” points out Jones. “File-based storage of data is the norm even under more relational models. [In “Big data added agility into a managed platform in a way that old school data warehouses just couldn’t,” stresses Jones.

Big Data 95

Big Data Big Data Apache Kafka Data Lakes 95

Pickl AI

SEPTEMBER 18, 2024

Data at Rest This includes storage solutions such as S3 Data Warehouse and Cassandra. These systems handle the storage costs associated with keeping vast amounts of content and user data. What Technologies Does Netflix Use for Its Big Data Infrastructure? How Does Netflix Ensure Security Against Fraud?

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Big Data Big Data Apache Kafka Big Data Analytics 52

AWS Machine Learning Blog

MARCH 30, 2023

For every xSaves prediction, it produces a message with the prediction as a payload, which then gets distributed by a central message broker running on Amazon Managed Streaming for Apache Kafka (Amazon MSK). The information also gets stored in a data lake for future auditing and model improvements.

Machine Learning 92

Machine Learning Machine Learning AWS ML 92

ODSC - Open Data Science

OCTOBER 9, 2024

What should you be looking for?

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Apache Kafka AI AI Machine Learning 40

Pickl AI

NOVEMBER 4, 2024

Additionally, Data Engineers implement quality checks, monitor performance, and optimise systems to handle large volumes of data efficiently. Differences Between Data Engineering and Data Science While Data Engineering and Data Science are closely related, they focus on different aspects of data.

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Data Engineering Data Engineer Data Engineering Data Engineering 52

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

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

Dataconomy

FEBRUARY 23, 2023

Solutions for managing and processing high velocity data Data engineers can use various solutions to manage and process high-speed data streams. 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.

Big Data 91

Big Data Big Data Data Engineering Data Engineer 91

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.

Database 52

Database Apache Kafka SQL AI 52

Pickl AI

DECEMBER 2, 2024

Real-time processing allows organisations to make timely decisions based on current data rather than relying on historical information.Technologies enabling real-time analytics include: Stream Processing Frameworks: Tools like Apache Kafka facilitate the continuous ingestion and processing of streaming data.

Big Data 52

Big Data Big Data Data Lakes Apache Hadoop 52

Pickl AI

JULY 20, 2023

Top 15 Data Analytics Projects in 2023 for Beginners to Experienced Levels: Data Analytics Projects allow aspirants in the field to display their proficiency to employers and acquire job roles. Implement real-time analytics to monitor trends or anomalies in the data.

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Pickl AI

JULY 24, 2023

Streaming Data Ingestion: Managing and processing data streams is the focus of streaming data ingestion, which was created expressly for this purpose. IoT applications, log processing, and other data-intensive scenarios frequently use this kind of ingestion.

Internet of Things 52

Internet of Things Apache Kafka ETL Azure 52

Pickl AI

JULY 8, 2024

Tools and Technologies to Minimise Latency and Optimise Performance Minimising latency is crucial for real-time data processing. Utilise in-memory data processing tools like Apache Kafka and Apache Flink, which provide low-latency data ingestion and processing capabilities.

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Data Pipeline Data Quality Database Apache Kafka 52

Pickl AI

AUGUST 9, 2024

APIs Understanding how to interact with Application Programming Interfaces (APIs) to gather data from external sources. Data Streaming Learning about real-time data collection methods using tools like Apache Kafka and Amazon Kinesis. Once data is collected, it needs to be stored efficiently.

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Big Data Big Data Big Data Analytics Big Data Analytics 52

Pickl AI

MARCH 19, 2025

Tools like Python, SQL, Apache Spark, and Snowflake help engineers automate workflows and improve efficiency. Learning these tools is crucial for building scalable data pipelines. offers Data Science courses covering these tools with a job guarantee for career growth. How is Data Engineering Different from Data Science?

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Data Engineering Data Engineer Data Engineering Data Engineering 52

AWS Machine Learning Blog

FEBRUARY 7, 2025

It is backed by Amazon Managed Streaming for Apache Kafka (Amazon MSK) (8). The next important step is to use these model results with proper analytics and data science. These results can also serve as a data source for generative AI features such as automated report generation.

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