Machine learning tool that is easy to learn and use

Rating: 9 out of 10

May 13, 2019

Use Cases and Deployment Scope

Currently, it is used for our information technology sector to implement machine learning features in-house. The idea is to explore models and perform some experimentation. It's used to find Machine Learning solutions for internal use in the company. The Microsoft resources in this tool make it easier to use machine learning, like the use of visual interfaces and how they manage deployment.

Pros

Visual interface
Possibility to track the IDs and also get the results from it
Charts to collect data and quickly check for performance/problems

Cons

Hard to apply Python code and run
More models could be available
Tableau interface would be perfect

Likelihood to Recommend

It is good to quickly and easily deploy a model for Machine Learning. It has a few coding aspects that enable machine learning that at first sight can be a problem for non-machine learning specialists. The system tries to gets the easiest results as possible.

It is less appropriate for complex systems and for detailed results to be analyzed.

Verified User

Team Lead in Information Technology (Machinery company, 10,001+ employees)

Vetted Review

1 year of experience

Azure ML: Most user friendly and the cheapest!

Rating: 10 out of 10

Incentivized

May 21, 2018

Use Cases and Deployment Scope

I was the president of an MBA class that used Azure ML to run analytics models. The tool was used by 40 students. We analyzed a few datasets to understand the tools, and afterward, we were able to create a few analytics products based on Azure ML.

Pros

User friendliness: This is by far the most user friendly tool I've seen in analytics. You don't need to know how to code at all! Just create a few blocks, connect a few lines and you are capable of running a boosted decision tree with a very high R squared!
Speed: Azure ML is a cloud based tool, so processing is not made with your computer, making the reliability and speed top notch!
Cost: If you don't know how to code, this is by far the cheapest machine learning tool out there. I believe it costs less than $15/month. If you know how to code, then R is free.
Connectivity: It is super easy to embed R or Python codes on Azure ML. So if you want to do more advanced stuff, or use a model that is not yet available on Azure ML, you can simply paste the code on R or Python there!
Microsoft environment: Many many companies rely on the Microsoft suite. And Azure ML connects perfectly with Excel, CSV and Access files.

Cons

Few models: Even though it has a lot of Machine Learning models, it is quite limited when compared to R. Most Data Scientists still use and prefer R, so the newest models tend to release as R libraries. With Azure ML, we need to wait for Microsoft to evaluate and decide if including a new model is a good idea or not
Tableau interface: last time I checked there was no easy way to connect with Tableau.
Cloud based: You always need a good internet connection to use it.

Likelihood to Recommend

Well suited:
- Run a machine learning model the fastest and easiest way;
- Working with an organization with no coding background;
- Trying to get the most of data the cheapest and easiest way possible;
- Introducing analytics and machine learning concepts to an organization or class;

Less appropriate:
- Running complex Machine Learning models;
- Visualizing data more deeply;
- Running new analytics models;
- Running heavy statistical models;

Gabriel Chiararia

MBA Candidate | Class of 2018 in Marketing at Brigham Young University Marriott School of Business (Consumer Electronics, 201-500 employees)

Vetted Review

2 years of experience

View profile

Azure ML: Most user friendly and the cheapest!

Rating: 10 out of 10

Incentivized

May 21, 2018

Use Cases and Deployment Scope

Pros

User friendliness: This is by far the most user friendly tool I've seen in analytics. You don't need to know how to code at all! Just create a few blocks, connect a few lines and you are capable of running a boosted decision tree with a very high R squared!
Speed: Azure ML is a cloud based tool, so processing is not made with your computer, making the reliability and speed top notch!
Cost: If you don't know how to code, this is by far the cheapest machine learning tool out there. I believe it costs less than $15/month. If you know how to code, then R is free.
Connectivity: It is super easy to embed R or Python codes on Azure ML. So if you want to do more advanced stuff, or use a model that is not yet available on Azure ML, you can simply paste the code on R or Python there!
Microsoft environment: Many many companies rely on the Microsoft suite. And Azure ML connects perfectly with Excel, CSV and Access files.

Cons

Few models: Even though it has a lot of Machine Learning models, it is quite limited when compared to R. Most Data Scientists still use and prefer R, so the newest models tend to release as R libraries. With Azure ML, we need to wait for Microsoft to evaluate and decide if including a new model is a good idea or not
Tableau interface: last time I checked there was no easy way to connect with Tableau.
Cloud based: You always need a good internet connection to use it.

Likelihood to Recommend

Gabriel Chiararia

MBA Candidate | Class of 2018 in Marketing at Brigham Young University Marriott School of Business (Consumer Electronics, 201-500 employees)

Vetted Review

2 years of experience

View profile

Azure Machine Learning Manufacturing Reviews & Insights

Azure Machine Learning Reviews

Machine learning tool that is easy to learn and use

Use Cases and Deployment Scope

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Cons

Likelihood to Recommend

Azure ML: Most user friendly and the cheapest!

Use Cases and Deployment Scope

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Likelihood to Recommend

Azure Machine Learning Reviews

Machine learning tool that is easy to learn and use

Use Cases and Deployment Scope

Pros

Cons

Likelihood to Recommend

Azure ML: Most user friendly and the cheapest!

Use Cases and Deployment Scope

Pros

Cons

Likelihood to Recommend