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Development

Featured in Development

From Research to Production With PyTorch

Jeff Smith covers some of the latest features from PyTorch - the TorchScript JIT compiler, distributed data parallel training, TensorBoard integration, new APIs, and more. He discusses some projects coming out of the PyTorch ecosystem like BoTorch, Ax, and PyTorch BigGraph. He digs into some of the use cases and industries where people are successfully taking PyTorch models to production.

All in development

Architecture & Design

Featured in Architecture & Design

An Engineer’s Guide to a Good Night’s Sleep

Increased microservices adoption, fueled by the move into the cloud where architectures and infrastructure can flex and be ephemeral, adds complexity every day to the systems we create and maintain. This takes place alongside operating models with autonomous and totally empowered teams, so each distributed system has its own tapestry of technical approaches, languages, and services.

All in architecture-design

AI, ML and Data Engineering

Featured in AI, ML & Data Engineering

Hands-on Feature Engineering for Natural Language Processing

Susan Li shares various NLP feature engineering techniques from Bag-Of-Words to TF-IDF to word embedding that includes feature engineering for both ML models and emerging DL approach. She covers the details including contextual & linguistic feature extraction, vectorization, n-grams, topic modeling, named entity resolution, which are based on concepts from mathematics, information retrieval, NLP.

All in ai-ml-data-eng

Culture & Methods

Featured in Culture & Methods

Randy Shoup on Creating High-Performance Cultures

In this podcast recorded at QCon London 2019, Shane Hastie, Lead Editor for Culture & Methods, spoke to Randy Shoup, VP of Engineering at WeWork about what is needed to create a high-performance culture.

All in culture-methods

DevOps

Featured in DevOps

Introduction to SMI (the Service Mesh Interface)

Brendan Burns talks about the generic interface for service mesh technology. The goal of this abstraction layer is to provide an easy-to-consume API that can be implemented by many different service mesh implementations (e.g. Istio, Linkerd, etc). Users are free to adopt service mesh concepts without being bound to any particular implementation. He covers the SMI specification and implementations.

All in devops

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Machine Learning for developers: 5 Essential Podcasts

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Data Access

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AI, ML & Data Engineering

Paypal's Hera Supports MySQL and Oracle DB Connection Multiplexing, Read-Write Split and Sharding

Srini Penchikala
on Jun 30, 2019
Java

Experimental Reactive Relational Database Connectivity Driver, R2DBC, Announced at SpringOne

Charles Humble
on Oct 01, 2018
DevOps

AppDynamics Launches New European Software-as-a-Service Offering

Helen Beal
on Jun 15, 2018
AI, ML & Data Engineering

PayPal's Gimel Analytics Platform Provides Unified Data API and GSQL

Srini Penchikala
on Apr 17, 2018
.NET

ORMs for .NET Core

Jonathan Allen
on Dec 04, 2017 13
Java

Apache OpenWebBeans Releases Meecrowave Server Version 1.0 for Java EE-Based Microservices

Michael Redlich
on Aug 30, 2017
AI, ML & Data Engineering

Managing Data in Microservices

Srini Penchikala
on Jun 28, 2017 2
AI, ML & Data Engineering

Data Preparation Pipelines: Strategy, Options and Tools

Srini Penchikala
on Apr 16, 2017
Java

Vulnerability in Java Reflection Library Fixed after 30 Months

Abraham Marín Pérez
on Apr 28, 2016 4
Java

Simplifying Database Queries with Jinq

Abraham Marín Pérez
on Mar 21, 2016 11
NoSQL

LinkedIn Open Sources PalDB, a Read-only Key-value Store

Abel Avram
on Oct 27, 2015

Presentations about Data Access

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Java

What's New in Spring Data

Christoph Strobl
on Feb 08, 2019

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29:29
Architecture & Design

From Content Management to Content Services with Spring Boot, Data and Content

Doug Hoke Paul Warren
on Jan 05, 2019

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31:38
Java

The New Kid on the Block: Spring Data JDBC

Jens Schauder
on Nov 13, 2018

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01:04:39
Java

Under the Hood of Reactive Data Access

Mark Paluch
on Nov 06, 2018

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46:00
Java

Reactive Relational Database Connectivity

Ben Hale
on Nov 06, 2018

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32:54
Java

JDBC, What Is It Good For?

Thomas Risberg
on Jun 16, 2018

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30:29
AI, ML & Data Engineering

Gimel: PayPal’s Analytics Data Platform

Deepak Chandramouli
on Jun 13, 2018

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49:00
Java

Simplifying Apache Geode with Spring Data

John Blum
on Jun 02, 2018

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44:16
Java

Under the Hood of Reactive Data Access

Mark Paluch
on Apr 01, 2018

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31:44
Java

Reactive Data Access with Spring Data

Mark Paluch Christoph Strobl
on Mar 10, 2018

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28:36

MORE PRESENTATIONS

Articles about Data Access

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AI, ML & Data Engineering

Columnar Databases and Vectorization

Siddharth Teotia
on May 27, 2018
DevOps

GDPR for Operations

Jon Topper
on Mar 10, 2018 1
DevOps

What Do Data Scientists and Data Engineers Need to Know about GDPR?

Andrew Burt
on Jan 27, 2018 3
Java

JPA 2.2 Brings Some Highly Anticipated Changes

Thorben Janssen
on Jan 25, 2018
Java

Introducing Reladomo - Enterprise Open Source Java ORM, Batteries Included! (Part 2)

Mohammad Rezaei
on Jun 13, 2017
DevOps

Q&A with Immuta on the Implications of EU’s General Data Protection Regulation (GDPR)

Manuel Pais
on Feb 10, 2017
.NET

Interview with Entity Modelling Tool Creator, Frans Bouma

Jonathan Allen
on Jan 06, 2017
.NET

Advanced Use Cases for the Repository Pattern in .NET

Jonathan Allen
on Oct 25, 2016 2
.NET

Implementation Strategies for the Repository Pattern with Entity Framework, Dapper, and Chain

Jonathan Allen
on Oct 14, 2016 4
.NET

Starcounter vs. ORM and DDD

Kostiantyn Cherniavskyi
on Aug 10, 2016 5
Metadata-Driven Design: Designing a Flexible Engine for API Data Retrieval

Aaron Kendall
on Apr 13, 2015

Guides about Data Access

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Resource Library

Why Use Redis Enterprise as a Database for your Microservices
One of the core principles of microservices architecture is the rejection of a monolithic application framework, which in turn favors the sharing of data between services rather than the use of a single large database...Read More.

Microservices with Redis Enterprise on Kubernetes
Are you adopting a microservices architecture, as a part of your application modernization effort or digital transformation journey? Do you understand the typical data problems you are likely to encounter, why are they different, and how can they be overcome?...Read More.

Redis Enterprise for Gaming
Redis is extensively used in gaming applications for ranking players in multi-player games through leaderboards, tracking player sessions with current statistics, and for caching to augment the capabilities of other datastores such as Cassandra, MongoDB...Read More.

Redis Enterprise for Financial Services
Redis is the high-performance database of choice across the finance industry for caching, full-text search, session stores, personalization, fraud mitigation and for processing time-sensitive financial transactions that require low latency...Read More.

Redis Enterprise on Intel's Persistent Memory
Redis Enterprise, a multi-model in-memory database, is optimized to take advantage of novel memory configurations based on Intel® Optane™ DC persistent memory...Read More.

Bloor White Paper - Multi-Model Database Technology For The 2020s
Redis What does it take for a database to thrive in the 2020s? According to Bloor Research, an independent research and analyst house, a database for the coming decade needs...Read More.

Developing Apps Using Active-Active Redis Enterprise
In this white paper, you will learn about how to develop apps using active-active Redis Enteprise with sample use cases and programs...Read More.

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