The phrase "availability of massive amounts" is correct and usable in written English.
It can be used when discussing the presence or accessibility of large quantities of something, often in contexts related to data, resources, or information.
Example: "The availability of massive amounts of data has transformed the way researchers conduct their studies."
Alternatives: "access to large quantities" or "presence of substantial amounts".
Deep Learning inherently exploits the availability of massive amounts of data, i.e. Volume in Big Data, where algorithms with shallow learning hierarchies fail to explore and understand the higher complexities of data patterns.
Because of the rapid generation of new data, availability of massive amounts of compute power and ease of use of new ML platforms (whether it is from large technology companies like Amazon, Google and Microsoft or from startups like Dato), we expect to see more and more applications that generate real-time predictions and continuously get better over time.
They are also in the midst of historic disruptions based on two factors: 1) the growth of the Internet – including its social and mobile extensions – as a new network for marketing, selling and distributing their products and services; and 2) the availability of massive amounts of new data generated by these industries, their customers and third parties that are relevant to them.
The availability of massive amounts of GWAS data has necessitated the development of new biostatistical methods for quality control, imputation and analysis issues including multiple testing.
The availability of massive amount of sequence data also stimulated in depth evaluation of the organization of the bacterial chromosome [ 5- 9].
The availability of massive amount of molecular bioactivity data creates rich new opportunities, yet for typical scientists involved in biomedical discovery research, the difficulty of processing and analyzing that data can often be a barrier.
A number of algorithms have been developed to accommodate analysis of massive amounts of RNA-Seq data.
Despite this, a major limitation involves the interpretation of massive amounts of microarray data.
Next generation sequencing (NGS) provides opportunities for cost-effective sequencing of massive amounts of DNA.
The availability of a massive amount of sequence data stimulated in-depth analyses on the organization of bacterial genomes [ 1- 6].
The availability of this massive amount of genome data has been both a boon and a major challenge for biologists.
