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TensorFlow 2 review: Easier machine learning
Now more platform than toolkit, TensorFlow has made strides in everything from ease of use to distributed training and deployment
The data lake is becoming the new data warehouse
Platforms like AWS Lake Formation and Delta Lake point toward a central hub for decision support and AI-driven decision automation
Time series analysis with KNIME and Spark
Train and evaluate a simple time series model using a random forest of regression trees and the NYC Yellow taxi data set
Supervised learning explained
Supervised learning turns labeled training data into a tuned predictive model
What is TensorFlow? The machine learning library explained
TensorFlow is a Python-friendly open source library for numerical computation that makes machine learning faster and easier
Hadoop runs out of gas
As big data customers flee complexity and embrace the cloud, the Hadoop vendors are sputtering
Natural language processing explained
Deep learning has improved machine translation and other NLP tasks by leaps and bounds
Deep learning explained
Deep neural networks can solve the most challenging problems, but require abundant computing power and massive amounts of data
4 reasons big data projects fail—and 4 ways to succeed
Nearly all big data projects end up in failure, despite all the mature technology available. Here's how to make big data efforts actually succeed
Machine learning explained
Able to learn from data, machine learning algorithms can solve problems that are too complex to solve with conventional programming
Machine learning algorithms explained
Machine learning uses algorithms to turn a data set into a model. Which algorithm works best depends on the problem
Delta Lake gives Apache Spark data sets new powers
A new open source project from Databricks adds ACID transactions, versioning, and schema enforcement to Spark data sources that don't have them
Pub/sub messaging: Apache Kafka vs. Apache Pulsar
Apache Kafka set the bar for large-scale distributed messaging, but Apache Pulsar has some neat tricks of its own
IBM preps Watson AI services to run on Kubernetes
IBM Watson services arrive in versions that can run on the public cloud or on privately hosted container infrastructure
How to use Azure Data Explorer for large-scale data analysis
Microsoft’s tool for querying terabytes of data finally arrives for everyone to use
Tutorial: Spark application architecture and clusters
Learn how Spark components work together and how Spark applications run on standalone and YARN clusters
Why you should use Gandiva for Apache Arrow
An execution engine for Arrow-based in-memory processing, Gandiva brings dramatic performance improvements to analytical workloads
Review: MXNet deep learning shines with Gluon
With the addition of the high-level Gluon API, Apache MXNet rivals TensorFlow and PyTorch for developing deep learning models
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