Laden...
July 19, 2019
Armed with big data, machine learning, predictive analytics, and unlimited data access, how do we limit the potential for harm? Read more â¶
Applying devops in data science and machine learning
NativeScript 6.0 speeds up builds, app updates
3 cost-cutting tips for Amazon DynamoDB
How to use .SD in the R data.table package
Kubernetes on AWS, Azure, and Google Cloud
How to deal with cloud complexity
The best machine learning and deep learning libraries
Based on a widespread industry survey, this IDG and Cradlepoint report reflects and explores the changing role of LTE in the enterprise. Read more â¶
Having data scientists collaborate with devops and engineers leads to better business outcomes, but understanding their different requirements is key Read more â¶
DEALPOST
Fill out forms, add signatures, and more with this innovative tool. Primary Site: Infoworld Read more â¶
Update to the JavaScript framework for building native iOS and Android apps also boasts smaller app binaries Read more â¶
How to avoid costly mistakes with DynamoDB partition keys, read/write capacity modes, and global secondary indexes Read more â¶
See how to use data.table's special .SD symbol to perform calculations and other tasks by group Read more â¶
How the managed Kubernetes services on the major clouds stack upâand how well they integrate with the clouds that host them Read more â¶
Cloud complexity may be inevitable, but a few strategies can help keep the chaos contained Read more â¶
TensorFlow, Spark MLlib, Scikit-learn, PyTorch, MXNet, and Keras shine for building and training machine learning and deep learning models Read more â¶
This report investigates where 5G is today, the significant and revolutionizing components of 5G, and how it will shape the future of networking. Read more â¶
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