Catalog Search Results
Author
Pub. Date
2023.
Language
English
Description
Learn about the scalability and manageability aspects of Apache Kafka and how to build asynchronous applications with Kafka and Java.
Scalable and distributed message queuing plays an important role in building real time big data pipelines. Asynchronous publisher/subscriber models are required to handle unpredictable loads in these pipelines. Apache Kafka is the leading technology today that provides these capabilities and is an essential skill for...
Author
Pub. Date
2023.
Language
English
Description
Learn about the fundamental concepts and basic operations of Apache Kafka, a leading technology for real-time streaming capabilities.
One of the key components of a big data processing pipeline is a scalable and distributed message queue. Message queues enable real-time streaming capabilities with multiple producers and consumers of data. This enables real-time applications that can analyze data and produce insights in a scalable fashion. Apache...
Author
Pub. Date
2023.
Language
English
Description
Get up and running with pretrained transformers in Hugging Face, the popular platform for natural language processing (NLP) applications.
Using pretrained transformers for natural language processing (NLP) has become extremely popular among ML engineers and data scientists. If you work in the field, or even have a role adjacent to it, you need to stay apace with the latest innovative tools. In this course, instructor Kumaran Ponnambalam shows you...
Author
Pub. Date
2021.
Language
English
Description
Learn about the fundamental concepts and basic operations of Apache Kafka, a leading technology for real-time streaming capabilities.
One of the key components of a big data processing pipeline is a scalable and distributed message queue. Message queues enable real-time streaming capabilities with multiple producers and consumers of data. This enables real-time applications that can analyze data and produce insights in a scalable fashion. Apache...
Author
Pub. Date
2020.
Language
English
Description
Solve common challenges in IT operations using the power of AI. Review use cases in the world of IT ops and learn how to apply AI technologies to address key problems.
IT operations is one of the key business functions for modern enterprises. As data centers become large, distributed, and integrated, the need to monitor and manage hardware, software, networks, and data increases exponentially. And while the elements in a network generate tons of...
Author
Pub. Date
2018.
Language
English
Description
Learn how to use Google Cloud Platform to train and deploy machine learning models for predictive analytics.
Predictive analytics use historic data to look forward, enabling organizations to make better decisions. However, making accurate predictions from big data can be an overwhelming task. Enter Google Cloud Platform (GCP), a suite of cloud-computing services that bring scalability, elasticity, and automated machine learning to predictive analytics....
Author
Pub. Date
2019.
Language
English
Description
Learn about the techniques for analyzing text data in Python and perform machine learning and predictions.
Text is a rich source of insights for businesses. Websites, social media, emails, and chats all contain valuable customer data. But to reap the rewards, you need to be able to analyze large amounts of unstructured text. Text mining is an essential skill for anyone working in big data and data science. This course teaches text-mining techniques...
Author
Pub. Date
2020.
Language
English
Description
Solve stream processing problems with Kafka Streams. Learn about using Kafka Streams and associated technologies to build stream-processing use cases leveraging popular patterns.
Stream processing is rapidly growing in popularity, as more and more data is generated every day by websites, devices, and communications. Platforms such as Apache Kafka Streams can help you build fast, scalable stream processing applications, but big data engineers still...
Author
Pub. Date
2018.
Language
English
Description
Discover how to select the right database for your data science project. Learn about the strengths and weaknesses of different database technologies and review specific use cases.
Over the past few years, the database world has seen a plethora of new database types appear: document, key-value, graph, and columnar. In addition, data science professionals also have the old giant—relational database management systems (RDBMS)—as an option. Typical...
Author
Pub. Date
2018.
Language
English
Description
Learn how to design and build data warehouses using Google Cloud Platform solutions such as BigQuery.
Cloud computing brings unlimited scalability and elasticity to data science applications. Expertise in the major platforms, such as Google Cloud Platform (GCP), is essential to the IT professional. This course—one of a series by veteran cloud engineering specialist and data scientist Kumaran Ponnambalam—shows how to design and build data warehouses...
Author
Pub. Date
2022.
Language
English
Description
Learn about various optimization and tuning options available for deep learning models and use them to improve models.
Deep Learning as a technology has grown leaps and bounds in the last few years. More and more AI solutions use Deep Learning as their foundational technology. Studying this technology, however, presents several challenges. IT professionals from varying backgrounds need a simplified resource to learn the concepts and build models...
Author
Pub. Date
2023.
Language
English
Description
Develop the skills required to architect and manage batch processing applications to generate consistent data-driven results.
Big data applications allow data scientists and analysts to acquire, store, manage, and use big data to generate more consistent, data-driven results. In this course, instructor Kumaran Ponnambalam explores real-world business use cases and best practices for architecting big data applications using existing open-source technologies....
Author
Pub. Date
2020.
Language
English
Description
Learn how to use Apache Flink relational APIs—the Table API and SQL—for batch and real-time exploratory data analytics.
Exploratory data analytics is a key phase in data science that deals with investigating data to extract insights. In a world of big data, exploring massive datasets is a challenge, since it requires technologies that are scalable, fast, and feature rich. Apache Flink—the popular stream-processing platform—is well suited...
Author
Pub. Date
2021.
Language
English
Description
Learn about the scalability and manageability aspects of Apache Kafka and how to build asynchronous applications with Kafka and Java.
Scalable and distributed message queuing plays an important role in building real time big data pipelines. Asynchronous publisher/subscriber models are required to handle unpredictable loads in these pipelines. Apache Kafka is the leading technology today that provides these capabilities and is an essential skill for...
Author
Pub. Date
2022.
Language
English
Description
Learn how to deploy and monitor machine learning models to deliver scalable, reliable ML products and services.
Suggested Prerequisites MLOps Essentials: Model Development and Integration Machine learning operations (MLOps) is one of the fastest growing subfields of artificial intelligence. In this course, instructor Kumaran Ponnambalam shows you how to deploy and monitor ML models to create structured, improved outcomes in your everyday workflow....
Author
Pub. Date
2017.
Language
English
Description
Learn about use cases and best practices for architecting real-time applications using big data technologies, such as Hazelcast and Apache Spark.
Real-time systems have guaranteed response times that can be sub-seconds from the trigger. Meaning that when a user clicks a button, your app better respond—and fast. Architecting applications under real-time constraints is an even bigger challenge when you're dealing with big data. Excessive latency...
Author
Pub. Date
2021.
Language
English
Description
Learn how to make Apache Spark work with other Big Data technologies and put together an end-to-end project that can solve a real-world business problem.
Data engineering is the foundation for building analytics and data science applications in the new Big Data world. Data engineering requires combining multiple big data technologies to construct data pipelines and networks to stream, process, and store data. This course focuses on building full-fledged...
Author
Pub. Date
2018.
Language
English
Description
Learn how to conduct exploratory data analytics on Google Cloud Platform.
Cloud computing brings unlimited scalability and elasticity to data science applications. Expertise in the major platforms, such as Google Cloud Platform (GCP), is essential to the IT professional. This course—one of a series by cloud engineering specialist and data scientist Kumaran Ponnambalam—shows how to conduct exploratory data analytics with GCP. First, review the...
Author
Pub. Date
2019.
Language
English
Description
Learn key techniques for cleansing and processing text in R, and discover how to convert text to a form that's ready for analytics and predictions.
Today’s big data and analytics pipelines are consuming more and more text data generated through websites, social media, and private communications. But deriving insights from text isn't straightforward; it requires a series of techniques and forms for preparing text for analytics and machine learning....
Author
Pub. Date
2021.
Language
English
Description
Discover how to use Apache Flink and associated technologies to build stream-processing use cases leveraging popular patterns.
Frameworks such as Apache Flink can help you build fast, scalable stream processing applications, but big data engineers still need to design smart use cases to achieve maximum efficiency. In this course, instructor Kumaran Ponnambalam demonstrates how to use Apache Flink and associated technologies to build stream-processing...
Didn't find it?
Can't find what you are looking for? Try our Purchase Suggestion Service. Submit Request