Ian Pointer
Ian Pointer is a senior big data and deep learning architect, working with Apache Spark and PyTorch. He has more than 15 years of development and operations experience.
InfoWorld’s 2019 Technology of the Year Award winners
InfoWorld editors and reviewers recognize the year’s best software development, cloud computing, big data analytics, and machine learning tools
The best open source software for machine learning
InfoWorld’s 2018 Best of Open Source Software Award winners in machine learning and deep learning
The best open source software for cloud computing
InfoWorld’s 2018 Best of Open Source Software Award winners in cloud computing
The best open source software for data storage and analytics
InfoWorld’s 2018 Best of Open Source Software Award winners in databases and data analytics
GKE tutorial: Get started with Google Kubernetes Engine
Discover how easy it is to create a Kubernetes cluster, add a service, configure autoscaling, and tap other great features of GKE
The 5 best programming languages for AI development
Which programming language should you pick for your machine learning or deep learning project? These are your best options
What’s new in Apache Spark? Low-latency streaming and Kubernetes
Continuous processing and native Kubernetes support in Apache Spark 2.3 spell the end for micro-batching and Hadoop
PyTorch tutorial: Get started with deep learning in Python
Learn how to create a simple neural network, and a more accurate convolutional neural network, with the PyTorch deep learning library
DIY GPU server: Build your own PC for deep learning
Building your own GPU server isn't hard, and it can easily beat the cost of training deep learning models in the cloud
Spark tutorial: Get started with Apache Spark
A step by step guide to loading a dataset, applying a schema, writing simple queries, and querying real-time data with Structured Streaming
What is Apache Spark? The big data analytics platform explained
Fast, flexible, and developer-friendly, Apache Spark is the leading platform for large-scale SQL, batch processing, stream processing, and machine learning
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