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What’s new in Julia: Version 1.0 is here
New package manager, better optimization debut in the first production release
Data is the lifeblood of AI, but how do you collect it?
AI and lots of good data go hand in hand, but it can be a challenge for companies to aggregate it
Deep Dive
Machine learning megaguide: Amazon, Microsoft, Databricks, Google, HPE, IBM
Download InfoWorld's massive roundup of Amazon, Microsoft, Databricks, Google, HPE, and IBM machine learning toolkits
Julia tutorial: Get started with the Julia language
Want the convenience of a dynamic language and the performance of a compiled statically typed language? Try Julia
Data is inherently messy. Is that really such a bad thing?
In an imperfect world, consider shifting your data quality mindset from “how do I clean all this up?” to “how do I make the most of this state of affairs?”
Why we lose out if we leave everything to algorithms
If we trust a measurement system wholly to data and algorithms, will it inevitably be gamed by the humans it measures?
How to build stateful streaming applications with Apache Flink
Take advantage of Flink’s DataStream API, ProcessFunctions, and SQL support to build event-driven or streaming analytics applications
Deep Dive
Quick guide: Learn to crunch big data with R
Get started using the open source R programming language to do statistical computing and graphics on large data sets
Practical use cases for real-time decisioning
Real-time decisioning has its place in almost every transaction and interaction you have with data and technology today
Introducing BigQuery ML for building predictive models with SQL
Google’s beta extension performs linear regression forecasting and binary logistic classification in the BigQuery data warehouse
Big data: enabling new approaches to IT infrastructure security
Big data technologies and advanced analytics, including AI, are promising a way to get ahead of cyber threats
video
R tip: Create maps in R
In this seventh episode of Do More with R, learn how to create maps in R—it’s easier than you think, thanks to new and updated packages like sf, tmap, and ggplot2
Deep Dive
Build an IoT analytics solution with big data tools
The Internet of things seems futuristic, but real systems are delivering real analytics value today. Here’s some real-world IoT advice from the field
3 big data platforms look beyond Hadoop
Learn how the Cloudera, Hortonworks, and MapR data platforms are evolving to meet the demands for real-time analytics and machine learning
Data lakes: Just a swamp without data governance and catalog
Most businesses’ data lakes are merely repositories of undefined data sets from multiples sources, resulting in data swamps
The importance of multitouch attribution: Why getting in the data weeds leads to better decision-making
As an organization, you want to understand if you’re making the right marketing investments. Smart enterprises follow a data-driven approach
What’s new in the Anaconda distribution for Python
Anaconda 5.2 adds job scheduling, support for GPUs, and integration with version control systems including Git and GitHub
Deep Dive
Download the Hadoop Deep Dive
Businesses are using Hadoop across low-cost hardware clusters to find meaningful patterns in unstructured data. In this in-depth PDF, InfoWorld explains how Hadoop works and how you can reap its benefits
Insights driving action: the quiet revolution
How insight-driven IT automation will become a competitive edge
PyTorch review: A deep learning framework built for speed
PyTorch 1.0 shines for rapid prototyping with dynamic neural networks, auto-differentiation, deep Python integration, and strong support for GPUs
How to get real value from big data in the cloud
Cloud computing makes big data affordable, but few companies know how to actually take actual advantage of it
video
R tip: Iterate with purrr's map_df function
In this sixth episode of Do More with R, learn how to apply a function to a vector of values and return a data frame
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