Top Rated MLJAR Alternatives
The way that auto ML works by managing data in tabular forms which improves efficiency in available hardware configurations Review collected by and hosted on G2.com.
It needs some better processing power i.e. Better hardware Review collected by and hosted on G2.com.
15 out of 16 Total Reviews for MLJAR
The time saved by using automatic ML application and the ability of model stacking to build more accurate Ml systems.it acts as an enhancement for existing data scientists. Review collected by and hosted on G2.com.
I don't see disadvantages in the technology in my personal opinion but i believe a counter opinion exists of how using such technology might one day end up replacing existing ml data scientists.
But if i have to point one out i would say during my work i have seen that inaccuracy is the biggest problem with current generation ML tools . Review collected by and hosted on G2.com.
MLJAR is one of the best python packages I have used so far for machine learning. The software is easy to install and very useful for developing new modules. Training the model on multiple algorithms is easy really on it, and the output is usually accurate and it hence saves tons of time in training and rerunning the model with different datasets in case of error. Review collected by and hosted on G2.com.
The product has worked perfectly fine for us so far, nothing to dislike here in particular, however more packages to the product would be highly appreciable. Review collected by and hosted on G2.com.
The AutoML feature is very easy to use and has similar syntax as sklearn module and report after it explained very nicely.
Although I am new to AutML I have used H2O but this is much easier as it has much simpler syntax and the results are better than sklearn and slighly better than H20. Review collected by and hosted on G2.com.
My only dislike is that It only has supervised algorithms as the popularity of unsupervised learning algorithms is growing because most of the data is unsupervised. Review collected by and hosted on G2.com.
MLJAR Supports a wide range of algorithms for classification along with support to a multitude of features for getting a better understanding of data through automated metric selection and feature engineering. Review collected by and hosted on G2.com.
MLJAR is still evolving and needs to keep pace with new advances in the science of machine learning techniques and procedures so that the outcomes from its data processing are more intuitive and applicable. Review collected by and hosted on G2.com.
The best thing about this package is easily share notebook and it allows others to execute parameters notebook and easy to download executed notebook as HTML or PDF files Review collected by and hosted on G2.com.
The thing i dislike the package is that the GUI of this .
It can be more user friendly to use and help people to understand the machine learning.
It's difficult to import in the python Review collected by and hosted on G2.com.
The main advantage of MLJAR is producing markdown reports from models training. Review collected by and hosted on G2.com.
The solution can quickly become complex and hard to visualize. It is hard to use version control systems because notebooks have code and output stored together in the notebook file. Review collected by and hosted on G2.com.
The best thing about MLJAR is that even the one having less or no programming background can even use it. It is easily sharebale and saves the development time of the developers. Also python notebooks can be converted to the the interactive web apps. Review collected by and hosted on G2.com.
Although MLJAR is a good and lightweight software but it can have updates more quickly. The beginner to advanced path can be more simplified so that everyone adapts to their env quickly. Review collected by and hosted on G2.com.
easy to write code - a graphical interface for code generation,
easy to reuse code as an application or scheduled task,
easy to control version,
easy to build applications with GUI,
easy to test. Review collected by and hosted on G2.com.
Couldn't figure out any dislike about it. Review collected by and hosted on G2.com.
One of the cases which I like is providing notebook parameters in YAML form. I never experienced this in any other product. Another one is scheduling a notebook execution. Review collected by and hosted on G2.com.
I am not satisfied with the user experience personally. I have used several platforms with ML integration which are far better. User experience needs some improvement. Review collected by and hosted on G2.com.
-It saves time due to a readymade package. Frankly speaking, it saves around 25% of time.
-Helps a lot in developing new module
-Easy to installation Review collected by and hosted on G2.com.
There is nothing I dislike about it. The only suggestion i can provide like More packages needs to be added for the popular product as well. Review collected by and hosted on G2.com.
