A Suitable software for Engineering Undergraduates

This is a good software which helps to solve statistical ptoblems,mathematical problems and also algorithm problems.so in Engineering there have lots of problems belongs to aforesaid kind of problems.so this can be useful for pre- Engineers.

Pros

This software gives most accurate answers and it has more sensitivity & most of values have precision.

Cons

sometimes error messages displaying while works are in progress

Data Science 101 Platform for non-IT people

It was the tool I learned the Data Science in the first place. So it is really good and intuitive with its graphical interface. For example you understand train-test split very well because you literally see the split as you work on it. As I progressed and needed more functions and more custom solutions, I started using Python scripts and solved it like that. So it gave me all these abilities.

Pros

- Its ease of use makes it possible for non-IT, non-developer, non-CS background people to make data manipulation, preprocessing, mining, visualization and modelling. - It has a graphical interface with nodes and connections so that you don't need to know Python/R to make predictive models or association rules/recommendation systems. - There's a vast library of functions - Even more functions are created by the community so non-existing customized functions are created by the community, via existing functions. - The visual flow of data makes it easy to understand and interpret it. - It teaches the CRISP-DM methodology in an intuitive way thanks to its graphical user interface - It can connect to SQL and similar servers so that the data can be read directly. - It is possible to write own Python/R script for custom needs.

Cons

- Custom needs are hard to carry out. - Functions have limited abilities and parameters - Data visualization is weak and relatively primitive - Model development is easy but deployment is hard - It is very slow unfortunately and I think this is KNIME's most important drawback

Knime - great tool for organizing data

It is a great program that it'll save you loads of time.

Pros

I really enjoy how easy is to transform data from multiple softwares (such as excel, SQL, etc) and manipulate on Knime.

Cons

Not user friendly for beginners, there is no clear path for learning the tool. However, as long as you start using it becomes easier.

Solid Platform for Small Datasets and Broad Data Connectivity

The two main reasons we used KNIME were to process and prep data, then to conduct machine learning by training models and processing predictions. KNIME is great with data prep and blend as long as the data set is small to medium in size (< 4GB). There were areas where we struggled and that was when models were more complex (> 50 variables) and being able to deploy and schedule jobs. We had to download JDBC drivers for our database connections, which was not something we had to do with other platforms.

Pros

There is a wide range of tools to process and prep data in the platform natively and additional tools that can be download within the platform. The ability to customize the settings for most of the tools allows the user to adjust the output. Even more technical settings, like hyperparameter tuning, can be done in the tool UI. There are numerous input and output options and types.

Cons

Pulling in very basic files, like Excel spreadsheets can be a bit challenging where other platforms handle files with ease. Also, database connections are not seamless. The Java memory errors also limit the size of data that can be processed without making manual adjustments to settings. Lastly, not being a cloud-based platform, processing big data is very time-consuming.

KNIME is very easy to learn and use for anybody

KNIME is a very good Data Analytics software overall. If the team can handle the slowness issue, it's great for both computer science associates and other employees.

Pros

There are multiple features that is great about KNIME. - It has a visual UI that does not require programming knowledge, where you connect nodes by drag and dropping but still do not lose the flexibility of programming languages because it has Python, R and JavaScript nodes too where you can write your own code. - Since it's a visual UI that you work on, it's possible to track down what's going on, similar to an ETL tool. That's something that does not exist on programming. - Community continuously develops Nodes so its like an organism that grows.

Cons

Its upsides come with downsides: - Since it's high level (so to speak in CS manner) software. It is far from computer language, and that makes it very slow. It gets even slower more nodes and extensions are installed which was again, an upside. - Nodes have customization and parameter management but they are not as customizable as Python/R libraries, though for that Python/R node can be used.