 Big Data and Machine Learning Special Report |
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| In this special newsletter we bring you up to date on all the new content and news related to Big Data and Machine Learning on InfoQ. |
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| Using NLP, Machine Learning & Deep Learning Algorithms to Extract Meaning from Text (presentations, Apr 02, 2017) | | Big Data Infrastructure @ LinkedIn (presentations, Apr 02, 2017) | | Using Deep Learning Technologies IBM Reaches a New Milestone in Speech Recognition (news, Mar 31, 2017) | | Building Pipelines for Heterogeneous Execution Environments for Big Data Processing (articles, Mar 31, 2017) | | Real-Time Recommendations Using Spark Streaming (presentations, Mar 30, 2017) |
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| Top Viewed Content on InfoQ |
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| Building Reactive Applications with Akka Actors and Java 8 (articles, Jan 23, 2017) | | Anomaly Detection for Time Series Data with Deep Learning (articles, Feb 11, 2017) | | Introduction to Machine Learning with Python (articles, Jan 28, 2017) | | RXJava2 by Example (articles, Feb 13, 2017) | | I Can't Believe It's Not a Queue: Using Kafka with Spring (presentations, Jan 29, 2017) |
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| Intel open-sources BigDL, a distributed deep learning library that runs on Apache Spark. It leverages existing Spark clusters to run deep learning computations and simplifies the data loading from big datasets stored in Hadoop. | | At QCon San Francisco, engineers at Netflix discussed their big data strategy and analytics infrastructure. This included a summary of the scale of their data, their S3 data warehouse, and Genie, their big data federated orchestration system. |
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| Google’s Multilingual Neural Machine Translation System creates an interlingua and translates between language pairs and phrases with no previous direct translation available, dubbed Zero-Shot translation. | | Google recently announced TensorFlow version 1.0. Python API is now stable and experimental APIs for Java and Go have been added. XLA delivers significant performance increase. Keras can also be integrated with TensorFlow using a build-in module. tf.transform, tf.layers, tf.metrics, and tf.losses all add new features to the framework. | | Beam exits incubation period and graduates to top-level Apache project, Google support and contribution to open source integration for various data processing backends and more. |
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| In this series, we give an introduction to some powerful but generally applicable techniques in machine learning. |
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| This article compares different alternative techniques to prepare data, including extract-transform-load (ETL) batch processing, streaming ingestion and data wrangling. |
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| Cassandra: The Definitive Guide, 2nd Edition book authored by Jeff Carpenter and Eben Hewitt covers the Cassandra NoSQL database version 3.0. InfoQ spoke with the co-author Jeff Carpenter. |
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| In this article, author discusses Apache Spark GraphX used for graph data processing and analytics, with sample code for graph algorithms like PageRank, Connected Components and Triangle Counting. |
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| This article addresses a few examples of issues when using machine learning to solve real-world problems and hopefully provides some suggestions (and inspiration) for how to overcome the challenges. |
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| Rajini Sivaram talks about Kafka and reactive streams and then explores the development of a reactive streams interface for Kafka and the use of this interface for building robust applications. |
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| Chun-Ho Hung and Nikhil Garg discuss Quanta, Quora's counting system powering their high-volume near-real-time analytics, describing the architecture, design goals, constraints, and choices made. |
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| Tom Gianos and Dan Weeks discuss Netflix' overall big data platform architecture, focusing on Storage and Orchestration, and how they use Parquet on AWS S3 as their data warehouse storage layer. |
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| Avi Kivity discusses ScyllaDB, the many necessary design decisions, from the programming language and programming model through low-level details and up to the advanced cache design, and more. |
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| Mike Olson presents several use cases where big data is collected and analyzed to gather insights from the automotive, insurance, financial, and other sectors. |
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