blog_posts: 315e9a7e7d
This data as json
id | createdDate | title | link | postExcerpt | featuredImageUrl | hash | contributors | modifiedDate | displayDate |
---|---|---|---|---|---|---|---|---|---|
blog-posts#34-3299 | 2018-02-26 17:11:58 | Build an online compound solubility prediction workflow with AWS Batch and Amazon SageMaker | https://aws.amazon.com/blogs/machine-learning/build-an-online-compound-solubility-prediction-workflow-with-aws-batch-and-amazon-sagemaker/ | Machine learning (ML) methods for the field of computational chemistry are growing at an accelerated rate. Easy access to open-source solvers (such as TensorFlow and Apache MXNet), toolkits (such as RDKit cheminformatics software), and open-scientific initiatives (such as DeepChem) makes it easy to use these frameworks in daily research. In the field of chemical informatics, many [...] | https://d2908q01vomqb2.cloudfront.net/f1f836cb4ea6efb2a0b1b99f41ad8b103eff4b59/2018/02/23/compound-solubility-v2-3-300x131.gif | 315e9a7e7d | Amr Ragab | 2018-05-25 20:19:43 | 26 Feb 2018 |
Links from other tables
- 11 rows from blog_post_hash in blog_post_tags