AI/ML Resources

ETL Pipeline to Analyze Healthcare Data With Spark SQL, JSON, and MapR-DB

Learn how to ETL Open Payments CSV file data to JSON, explore with SQL, and store in a document database using Spark Datasets and MapR-DB.

November 23, 2017

by Carol McDonald

· 17,638 Views · 7 Likes

Handling Character Data for Machine Learning

Learn about different methods of encoding character attributes for creating useful machine learning models, including frequency-based encoding and hash encoding.

November 21, 2017

by Sibanjan Das

· 29,368 Views · 7 Likes

How to Use Kubernetes to Quickly Deploy Neo4j Clusters

When we first created the Kubernetes templates, I wrote a blog post about it. In the comments, someone suggested that we should create a Helm package for Neo4j. 11 months later… we have it!

November 20, 2017

by Mark Needham

· 8,465 Views · 1 Like

Finding the Floor and Displaying Holograms at Floor Level in HoloLens Apps

What if you could simply stare at a place below your head and say "yes," and a white plane would appear exactly on the ground? Here's how to make it happen.

November 14, 2017

by Joost van Schaik

· 15,312 Views · 2 Likes

Feature Engineering for Deep Learning

Many DL neural networks contain hard-coded data processing, along with feature extraction and engineering. They may require less of these than other ML algorithms, but they still require *some*.

November 9, 2017

by Jean Francois Puget

· 23,017 Views · 5 Likes

NGINX and IoT: Adding Protocol Awareness for MQTT

Buckle up for a 30-minute talk about the current state of IoT data and a demo that tackles MQTT, TLS, load balancing, session persistence, and plenty more.

Updated November 8, 2017

by Liam Crilly

· 16,316 Views · 4 Likes

Feature Hashing for Scalable Machine Learning

Feature hashing is a valuable tool in the data scientist's arsenal. Learn how to use it as a fast, efficient, flexible technique for feature extraction that can scale to sparse, high-dimensional data.

November 8, 2017

by Nick Pentreath

· 19,234 Views · 3 Likes

Optimizing K-Means Clustering for Time Series Data

Given the amount of data we collect, faster clustering times are crucial. Here's how we sped up our k-means clustering process!

October 30, 2017

by Jason Snell

· 26,191 Views · 2 Likes

Java: The Strategy Pattern

This deep dive into the classic Strategy pattern covers how it works, example usage, and deciding how and when to use it in your projects.

October 29, 2017

by Justin Albano

CORE

· 82,194 Views · 66 Likes

Dockerizing, Clustering, and Queueing Up With Mule Enterprise

In this tutorial, you'll learn how to build Mule instances and cluster instances, and Dockerize a Mule application to run in a container.

October 28, 2017

by Anirban Sen Chowdhary

· 10,594 Views · 5 Likes

Machine Learning Algorithms: Which One to Choose for Your Problem

Many articles about machine learning algorithms provide great definitions — but they don't make it easier to choose which algorithm you should use. Enter: this article!

October 27, 2017

by Daniil Korbut

· 26,703 Views · 34 Likes

How Neo4j Is Making Graph Technology More Accessible

In today's news: Neo4j is announcing Cypher for Apache Spark and the Neo4j Native Graph Platform. Come learn about it all, according to Neo4j's Head of Product Marketing.

October 24, 2017

by Tom Smith

CORE

· 5,695 Views · 2 Likes

Learning Neural Networks Using Java Libraries

Learn about the evolution of neural networks and get a summary of popular Java neural network libraries in this short guide to implementing neural networks from scratch.

October 22, 2017

by Daniela Kolarova

CORE

· 23,194 Views · 20 Likes

Reinforcement Learning for the Enterprise

Reinforcement learning is a first step towards artificial intelligence that can survive in a variety of environments instead of being tied to certain rules or models.

October 21, 2017

by Sibanjan Das

· 15,568 Views · 8 Likes

Changing Attitudes and Approaches Towards Privacy, AI, and IoT

Big data, IoT, and AI have all contributed to the widespread use of personal info. The privacy debate is at a crossroads where the public, authorities, and companies must decide in which direction the industry will turn.

October 20, 2017

by Ira Pasternak

· 9,560 Views · 6 Likes

AI-Powered NLP: The Evolution of Machine Intelligence From Machine Learning

With the advent of deep learning techniques, MI objectives like automated real-time question-answering, emotional connotation, fighting spam, and more are achieved.

October 19, 2017

by Tuhin Chattopadhyay

CORE

· 13,559 Views · 6 Likes

An Introduction to Caching: How and Why We Do It

When it comes to caching, what was once a nice-to-have it now a must-have. Check out this detailed article to learn everything you need to know about caching!

October 19, 2017

by Arun Tawara

· 172,751 Views · 47 Likes

TensorFlow for Real-World Applications

TensorFlow and deep learning are things that corporations must now embrace. The coming flood of audio, video, and image data and their applications are key to success.

October 17, 2017

by Tim Spann

CORE

· 32,654 Views · 10 Likes

Using Machine Learning to Retrieve Relevant CVs Based on Job Description

If you've ever tried to hire anyone, you know how difficult it can be to pour through hundreds of resumes and find the right one. AI can take the pain out of the process!

October 16, 2017

by Francis C. Fernandez-Reyes

· 51,185 Views · 14 Likes

Stream Processing With Apache Flink

See how to get started with writing stream processing algorithms using Apache Flink. by reading a stream of Wikipedia edits and getting some meaningful data out of it.

October 16, 2017

by Ivan Mushketyk

· 20,536 Views · 9 Likes

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