Top Rated Apache SystemML Alternatives
I like best about Apache SystemML is its semaless scalability from single machines to large cluster and its integration with Apache Spark for Efficent big data processing. Review collected by and hosted on G2.com.
I dislike about Apacke SystemML is its steep learning curve for beginners. It requires users to be confertable with coding and big data frameworks,which can be challenging for those new to machine learning or big data tools. Review collected by and hosted on G2.com.
5 out of 6 Total Reviews for Apache SystemML
Apache SystemML is from IBM which declared it as open source. Apache SystemML is good platform to solve Machine Learning problems. In Machine Learning we need of a lot of data and handling those bigdata is not an easy task which can be done seamlessly with Apache SystemML. It is also helpful for data scientist or engineers. It customizes and optimizes algorithms based on there characteristics. It supports popular R, Python language which is helpful also. With the add on help of apache spark it flourish it's accuracy well. Apache SystemML automatically generate hybrid runtime plans ranging from single node, in memory computation, distributed computation on Apache Hadoop and Spark. Review collected by and hosted on G2.com.
Apache SystemML is still struggling for customer acquisition. Also it lacks of project collaboration. Sometimes it seems slow while processing data. Though there is documentations but it needs an update periodically. Review collected by and hosted on G2.com.
I like that Apache SystemML lets you write ML models in a simple way and handles the complex details of execution and scaling for you. Review collected by and hosted on G2.com.
Another downside is that Apacke SystemML can be less flexible for customer ML algorithms compared to lower-level libraries, and its performance may vary based on how well the automatic optimization align with specific use cases. Review collected by and hosted on G2.com.
So machine learning deals with a huge amount of data, right? Apache SystemML is kind of a platform that dives right into this, focusing mainly on the big data needed to create some machine learning modules. And believe me, it still runs on Apache Spark, which gives the whole thing a boost in accuracy. Review collected by and hosted on G2.com.
I have been having problems with the lack of documentation. Review collected by and hosted on G2.com.
As we know the machine learning is deals with the Big Data so in the Apache SystemML is a platform who mainly focus on the bigdata that is require to create a machine learning module. So that will have the more accuracy.It can be run over the apache spark. Review collected by and hosted on G2.com.
Dont have the complete guide documentation also not highly available. Review collected by and hosted on G2.com.
