Tag: TensorFlow
Jun 25, 2018 |
Building high-quality artificial intelligence (AI) is hard work. It’s a specialized discipline that historically has required highly skilled specialists, aka data scientists.
Any time you require some highly skilled, highly paid practitioner to accomplish something of value, you’ve introduced a bottleneck into that process. Read more…
Jun 5, 2018 |
Databricks today unveiled MLflow, a new open source project that aims to provide some standardization to the complex processes that data scientists oversee during the course of building, testing, and deploying machine learning models. Read more…
Jun 5, 2018 |
The folks behind Apache Spark today unveiled Project Hydrogen, a new endeavor that aims to eliminate barriers preventing organizations from using Spark with deep learning frameworks like TensorFlow and MXnet. Read more…
May 31, 2018 |
A drug discovery technique called “high content” screening analyzes data in microscopic images used to determine the effects of genetic and chemical treatments on cell cultures. However, the processing-intensive analysis of sets of thousands of pre-defined features can take half a day. Read more…
May 21, 2018 |
As the amount of machine learning training data soars, so too does demand for new tools that will accelerate the process. With that in mind, Google Cloud announced the beta release of a new feature that allows users to speed training by running Tensor processing units (TPU) on its machine learning engine. Read more…
Apr 18, 2018 |
Don’t look now, but Presto, the SQL engine developed by Facebook as a follow-on to Hive, is starting to catch on in a big way. According to a new survey of big data-as-a-service customers by Qubole, Presto logged impressive usage gains during 2017, and outgrew Hive and Spark across many metrics. Read more…
Feb 21, 2018 |
A startup named ParallelM today unveiled new software aimed at alleviating data scientists from the burden of manually deploying, monitoring, and managing machine learning pipelines in production.
Dubbed MLOps, ParallelM‘s software helps to automate many of the operational tasks required to turn a machine learning model from a promising piece of code running nn Spark, Flink, TensorFlow, or PyTorch processing engines into a secure, governed, and production-ready machine learning system. Read more…
Feb 13, 2018 |
Organizations storing big data in Snowflake’s cloud data warehouse can now run machine learning and deep learning algorithms against that data thanks to a new partnership with Qubole.
The two companies today announced a partnership that will allow Qubole’s big data processing engines, including Apache Spark and TensorFlow, to read and write data to Snowflake’s data warehouse. Read more…
Nov 9, 2017 |
Deep learning has emerged as a cutting-edge tool for training computers to automatically perform activities like identifying stop signs, detecting a person’s emotional state, and spotting fraud. However, the level of technological complexity inherent in deep learning is quite daunting. Read more…
Jun 28, 2017 |
Companies that want to use TensorFlow to execute deep learning models on big data stored in Hadoop may want to check out the new SmartAI offering unveiled by Datameer today. Read more…
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