Orange

Machine Learning, Perdiction based data viulization

Kommentare: Used in human resource planning, need of training in human resource development.
Analyzed visuals of unemployment vs employed life's essential to get motivational reforms.
Used in finance settlement predictions.

Vorteile:

Best ever tool to visualize large data with basic configuration even by UI steps, like data flows and variable flows. Much effective in statistic process control, prediction and forecasting. It’s my essential tool while planning and deep through into large data, Machine learning and prediction models are awesome usage while testing hypothesis models. User interface, graphs, are really helpful to determine full meaning of data, so in data mining and data science it is a worthy tool with cool UI with easy usage. Machine learning, data prediction further can be used with programming in AI and other automated detection tools. Performance is awesome working on data, very easy to install.

Nachteile:

Live visualization can’t be obtained from a database or data source, somehow it should be linked like simulated tool, like graph is running as data changing. Saas, domain or remotely usage is not available. Graphs can’t be further used in another presentation with data source, a screenshot is only can be copied.

Free and Simple beginners data analysis

Vorteile:

A great and accessible free to use software that helps analysts get started with visual analysis and exploration.

Nachteile:

It can be hard to find errors in the data as you have to trawl the data manually to find them, does not always scale with large scale sheets

easy product selection, order, and checkout, to convenient online payment, shipping, and delivery—e

Kommentare: It's a good platform

Vorteile:

Everything you need to start online today grow your business

Nachteile:

No one can buy during site crush Can't try before buy Highly competitive

An Amazing Tool for Data Visualization, Machine Learning and Data Mining

Kommentare: That's splendid. I want to sincerely thank you. A great tool for researchers, scientists, Master's and PhD students, data scientists, and everyone who is keen on Data Mining, Machine Learning and Data Visualization.

Vorteile:

I was using this program when I was doing my first Master's in Fundamental and Applied Linguistics, and the software turned out to be indispensable for my qualitative and quantitative research. I used the tool for lots of different operations, such as Linear Regressions, K-Means Clustering, working with Heat Map, Venn Diagram, t-SNE, Text Preprocessing, Topic Modelling, Concordance and Sentiment Analysis as well as working on Correlations and Data Tables. The most pleasant thing was that this software is compatible with Linux (mine was Ubuntu), but for some weird reason it worked better on Windows despite it should have liked more the native Python environment. However, it is really an outstanding tool, I really appreciate this great thing. I think it would be good if the developers worked on creating a more powerful version with paid subscriptions. Just an idea for the guys to consider in the future.

Nachteile:

I had experienced some problems with doing Sentiment Analysis using by Orange (there were some widget or plugin trouble, for some weird reason the Sentiment Analysis thing was working perfectly only with some specific sets of data and languages).

Orange is for non programmers who want to learn Machine Learning!

Kommentare: Overall my experience with Orange has been fruitful for me as I picked up machine learning concepts without allowing my basic coding knowledge to hinder me. The interface is prettier than weka(another GUI tool for machine learning) There are several preloaded datasets that has already been clean and users can take advantage of those and follow through the documentation that is provided. My favorite one is the titanic dataset that predicts if the person survives or not depending their gender, class and the number of siblings/spouses they have.

Vorteile:

The graphical user interface of orange is great for someone who is not a programmer but wants to execute analytic workflows on machine learning on their dataset. The interface is nicely designed and the analytics workflow is easy to create with the use of drag and drop of its widgets. The widgets available are extensive and would enable users to clean, visualize, build models for supervised and unsupervised learning and validate their model. Orange has put together resources for its users to pick up machine learning on their own. There are also several tutorial videos as well on the website.

Nachteile:

We aren't able to set.seed in the software which causes results and analysis to not be reproducible. Orange does not provide enough parameters to tweak for advanced users. For instance, the randomForest widget does not allow the user to see which variables have the highest information gain.

Business Statistics on visualization and Machine learning with Orange

Kommentare: Overall an effective tool for business to analyze statistics by visualization, specially a few clicks can conclude million/billion of records and hence you can proceed,optimise and decide the business/project scenioris.
Effective usage by predictions and categorised machine learning in AI.

Vorteile:

Best tool to perform visual analyze the deep statistics of a large data with a few steps, easy to use, UI is accordingly designed. Faster in operation with recommended system specification. Data input format is optimisation based and easier to conclude the prediction results. Supervised/unsupervised Machine learning is easier through basic programs. Best fo forecasting,predictions,SPCs.

Nachteile:

Not such a cons I found it, but only it can not configured with live data, any attachment with Mysql DB would be a plus point to work on live visualization.

Excellent Opensource for Data Analysis & Visualization

Kommentare: Overall, I am very satisfied with Orange opensource for its data visualization and analysis features and would recommend it to others.

Vorteile:

For working on large data and statistical parameters including, predictive/hypothesis models and regression models this opensource provides efficient solution. Very convenient in performance, Data can be input in many formats, like .csv excel table, even a .sql format file can also be used. Graphical analysis of large data can be obtained with few steps, like scatter diagram add file, select scatter chart or any other, and variable, hence billion of records graphical representation can be obtained. Machine learning supervised, unsupervised and data categorized models and their validation is much sophisticated in Orange.

Nachteile:

Graphics can’t be copy/pasted in raw form in any presentation. Analysis and prediction of live data is not facilitated in orange. Errors are not categorized and authenticated by numbers.

Pros and Cons of orange for Data visualization

Kommentare: A perfect suit for business statistics, prediction analysis, machine learning and data visualization.
Uses low resources, fast and convenient.

Vorteile:

Easy to use and understand to perform the visualization work with large data, purely assists you to predict business insights with machine learning. Graphics and analysis direct you clearly to conclusions/results . As large data reading is tough and to make conclusion with the raw data is much tough so tools like orange will really help, it is based in data flows configuration which is too handled by user interface. Machine learning models and anylsis can be too performed on it for roboting.

Nachteile:

Graphics controller are lesser like zoom,scroll. 2nd they can't be exported in visual form. Reliability effects when wrong data is provided but it can't detect like numbers format instead of alphabatic letters.

Data Analysis and ML with data Visulization.

Kommentare: Overall good to use if you are expert, data mining,visulization on big data I found perfect but after many practices, mixed GUI and programming so analysis is easy by setting the data flows. in this cost it is better.

Vorteile:

Useful tool to analyse big data, while working with regression and hypothesis I found it very helping. perdiction result may be conluded accurately if we know best assigning and configuration of data sets. Machine learning practies can be determined with basic programming.

Nachteile:

Advance analysis is not so easy, it do not give any error even on wrong data. some times slower the system while working on data.

Business anayltics and data visulization with Orange

Kommentare: Overall found very useful and sophisticated, it fullfilled all my requirements which were comletely based on SPC and forecasting.
On a few clicks I can analyze/visulize million of records within very short time. Recommended for Planning and forecastng purposes.

Vorteile:

A powerful tool to analyze,perdict and visualize large data with a few configuration of data varibales, smooth and fast while working. Forecasting, trends can be simulated by visualization on it. Graphs settings are not typical that are fixed, In Orange we can modify axis,scale and data accordingly.

Nachteile:

Charts, visulized items cant be exported or copied in raw form, only screen short etc. is captured, which is some how does not look better when resizing in a presentation. Tracing error in data is difficult becuase we have to see it manual.

Effective usage of data Visualization and Statistical ML models.

Kommentare: Overall found it useful while working on raw data, used in designing Electrical consumption of appliances, and assessment.

Vorteile:

Used in big data analysis, found extremely easier while getting data insights and prediction with a few basic configurations, graphs, charts of external data like excel, CSV, and MySQL table are supported to perform. Machine learning and statistical-based machine learning models are useful while working with AI/automation-based analysis, data flow with variables can be defined as draggable options, no huge coding is required, while for advanced scenarios coding options is also available.

Nachteile:

Graphics are poor formats, poor functions in charts, like histogram can not be modified after putting the data and variables, while even in excel its is configurable, support with ERPs is not available, some APIs type configuration should be available to work on ERPs data/

Forcasting,Business analysis and Data Visualization suit to Drive your Business

Kommentare: Its good for intermediate users but advance analysis cannot performed with current tools. there must be some additional tools for advance tools as mentioned above.

Vorteile:

An impressive software for event forcasting based on stats and company qualitative variables.Orange have amazing graphics and data visualization that can alert you about business performance. The most desireable thing, huge data can be manage and visualise different ways according to the business requirement.

Nachteile:

There must be some econometric tool to pridict and analyze both qualitative and quantitative data. Graphs and charts cannot exported, An auto error alert must be there for smoth and efficient working.

Orange Tool for business data visualization and analytics

Kommentare: over satisfied and achieved goal by using orange.

Vorteile:

Data visulization of big data takes much lesser time to give output, many input formats are suported like .sql, .csv excel and notepad. supervised and unsupervised machine learning based application can be made easily. for data analytics by visulization is efective.

Nachteile:

Not cloud based service available, cant be connected with web or erp, no api working available like other tools.

Data analysis and machine learning techniques with orange

Vorteile:

Large data reading by visuals is essential tool is data science, perdiction and analyasis. Orange provides effective data analysis by visuals, it has smart UI to build machine learning and perdiction models. Machine learning catogrization, perdiction and analysis are used in data science and data mining, so we professional adopt it in our data mining project, some times its essential part of tools. Data flows, by UI can be set, and results can be obtained accordingly,machine learning models can be accessed,controlled and configured with basic codes.

Nachteile:

Not smooth while facing an error, saas plate form is not available, live graphs are not available, i.e we cant work with it with live data, databases like oracle is difficult to configure, so via excel large data takes much time.

Orange companion to work on data visualization

Kommentare: The tool while working on statistics and data visualization provides best predictions based supervised/unsupervised machine learning.

Vorteile:

Best data visualization tool to work on data and statistics with machine learning tactics. Statiatics and perdiction based scenerios can be solved easily on it, handel defined/undefined variable to get optimum results, import from excel, sql csv is good thing to work on external data.

Nachteile:

Graphics poor, like charts etc, cant be embeded into another editors, takes time and uses much system resources.

Data Management and visualisation

Kommentare: Its too impressive,Big data can managed easily. i manage billion of enteries and analysied it in different aspects.

Vorteile:

GUI of orange is very impressive, Specially designed for non programmer. Its very easy to summarize huge data.its open source and data mining tool kit is worthful.Data can be analysied by regression analysis.

Nachteile:

Graph and charts cannot be export directly from orange.There must be advance economatric tool for analysis.

Choosing the best Machine Learning Made Easy

Kommentare: Identification of the best ML processes to use for predicting energy market price dynamics.

Vorteile:

Orange is a comprehensive machine learning and AI platform that is easy to use and provides the ability to test and compare different modalities of ML and AI to quickly see which perform best. Its simple drag and drop and wire together workflow is intuitive. It tight python integration is a great extender.

Nachteile:

Neural network support lags behind other methodologies at this time.

Orange is a very useful tool for data analysis

Kommentare: So far it has helped me to complement my knowledge in the area of data management and analysis

Vorteile:

It has a very friendly interface. It provides different elements for data visualization. In addition to having a simple and understandable interface offers several elements such as python scripts that allow you to make developments that complement or allow to manage and analyze data in a better way.

Nachteile:

The file loading section seems to be the only one that lacks visual help. However, I think it is a good application.

User Friendly Software

Vorteile:

Software is user friendly and can be understand with a minimum supervision

Nachteile:

at this stage, everything is doing well using this software