BigML is a machine-learning platform designed to make machine learning more accessible to businesses and individuals. It brings together tools for data exploration, visualization, feature engineering, and building and deploying models to support predictive analytics.

What languages does BigML support?

BigML supports 1 language: English.

What company sizes and industries is BigML the best fit for?

BigML appears most aligned with small businesses, with mid-market teams also represented; Computer Software is the most prominent industry. The reviewer-reported segments cluster around these groups:

Company size — Small business: Teams with 50 or fewer employees make up the strongest segment.
Company size — Mid-market: Teams with 51–1,000 employees are also represented.
Industry — Computer Software: This is the most prominent industry segment.

How long does it take to implement BigML across a team?

Implementation most commonly takes 1–3 months, though reported time to go live varies. The other reported ranges include shorter and longer implementations.

Time to go live	Relative frequency
1–3 months	Most common
Less than 1 month	Also reported
3–6 months	Less common
Less than 1 day	Occasional

What customer support options does BigML provide, and how do users find the overall support experience?

BigML provides support through chat, and the support experience comes across as solid but not uniformly exceptional. Users who describe specific support interactions appreciate prompt help resolving issues.

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Prabhat G.

Software Engineer

Computer Software

Small-Business (50 or fewer emp.)

12/3/2017

"Machine Learning on the fly"

4.5/5

What do you like best about BigML?

It provides easy to use APIs for machine learning algorithms as well as can be used a cloud storage for managing ML data, might be some dataset or a custom algorithm. Review collected by and hosted on G2.com.

What do you dislike about BigML?

All the APIs require a internet connection, won't work for offline systems. Some kind of offline support is required. Review collected by and hosted on G2.com.

Recommendations to others considering BigML:

There are various datasets provided and several examples too, I advise to have a look on them to help you understand how bigML works. Review collected by and hosted on G2.com.

What problems is BigML solving and how is that benefiting you?

Using bigML APIs for machine algorithms that might otherwise need us work more on ML part not the project. Review collected by and hosted on G2.com.

Current UserValidated ReviewerIncentivizedSource: G2 invite

Richa R.

Software Engineer

Computer Software

Small-Business (50 or fewer emp.)

1/10/2018

"Great Machine Learning API"

5/5

What do you like best about BigML?

Along with algorithms it also provides a lot of data sets, which really helps one to understand how it really works and directly get hands on with the service. Review collected by and hosted on G2.com.

What do you dislike about BigML?

It offers very less perks for example: very storage space with the free account, there should be more perks provision with the free account. Review collected by and hosted on G2.com.

Current UserValidated ReviewerIncentivizedSource: G2 invite

Aarohi G.

CEO

Computer Software

Small-Business (50 or fewer emp.)

11/3/2017

"Cloud Storage + ML Algorithms in one package"

4.5/5

What do you like best about BigML?

- Available algorithms that can be used by simple API support.

- There also different datasets available that can be used to train basic models.

- Cloud Storage.

- Supports multiple languages. Review collected by and hosted on G2.com.

What do you dislike about BigML?

Cannot work offline, everything works on web based API which requires internet. For even simple changes I need internet connection. There should be offline support. Review collected by and hosted on G2.com.

Recommendations to others considering BigML:

There are not enough tutorials available, if you are a learner use scikit-learn. It's better has a good documentation as well as many tutorial videos are available on internet. Review collected by and hosted on G2.com.

What problems is BigML solving and how is that benefiting you?

- Building machine learning based products using BigML API.

- Using cloud storage feature to store trained models. Review collected by and hosted on G2.com.

Current UserValidated ReviewerIncentivizedSource: G2 invite

Rishab G.

CEO

Computer Software

Small-Business (50 or fewer emp.)

10/28/2017

"Cloud repository for Machine Learning models and much more"

5/5

What do you like best about BigML?

- Cloud storage feature, where you can store your trained models and data sets, which can be used anywhere just with the access of internet.

- The tutorials, it is a great help! Review collected by and hosted on G2.com.

What do you dislike about BigML?

The whole framework is API based so you cannot play with the data when you are offline. It is a major issue I am facing all the time. Review collected by and hosted on G2.com.

Recommendations to others considering BigML:

If you are a learner first try scikit-learn or some other better library, as BigML doesn't provide offline support and more of a professional kind. Review collected by and hosted on G2.com.

What problems is BigML solving and how is that benefiting you?

- Maintaining and managing Machine Learning models.

- Developing ML based projects using the API, which is very simple to use. Review collected by and hosted on G2.com.

Current UserValidated ReviewerIncentivizedSource: G2 invite

Melanie C.

Founding Partner

International Trade and Development

Small-Business (50 or fewer emp.)

12/2/2017

"Lots of data and easy to use (so far)"

3.5/5

What do you like best about BigML?

We're still implementing but so far so good, we like the amount of predictive modules we can set up which will help us layer data for mapping and outreach into the communities we work in. Review collected by and hosted on G2.com.

What do you dislike about BigML?

So far nothing other than making sure we don't have an operator error during our set up to ensure we get the right predictive output. Review collected by and hosted on G2.com.

What problems is BigML solving and how is that benefiting you?

We hope to use bigML in our research project that is currently focused in an urban area of over 1 million people. Part of what we hope to use bigML to do is predict technological (internet) usage based on survey data we collect over 5-9 months. The outcomes we hope will allow us to develop recommendations (policy and planning) to local governments, public institutions, and citizens. Review collected by and hosted on G2.com.

Validated ReviewerIncentivizedSource: G2 invite

Tejasvini V.

Software Engineer

Computer Software

Small-Business (50 or fewer emp.)

Updated 11/12/2017

Originally submitted 11/2/2017

"Machine Learning with BigML"

4.5/5

What do you like best about BigML?

- Support for cloud storage.

- Sample datasets provided.

- It has implemented algorithms for clustering and classification that can be used through API. Review collected by and hosted on G2.com.

What do you dislike about BigML?

- In the free pack it offers very less storage and also limits the number of tasks.

- Whole framework is API based and has no offline support. Review collected by and hosted on G2.com.

Recommendations to others considering BigML:

Use scikit-learn before using bigML. It has good documentation and a lot of tutorials available on internet. Review collected by and hosted on G2.com.

What problems is BigML solving and how is that benefiting you?

- Using as a cloud storage for trained models and datasets so I can remotely access them.

- Using API of different algorithms to develop applications. Review collected by and hosted on G2.com.

Current UserValidated ReviewerIncentivizedSource: G2 invite

Haripreet R.

Senior Software Engineer

Computer Software

Small-Business (50 or fewer emp.)

12/5/2017

"Elevate Machine Learning Experience"

5/5

What do you like best about BigML?

Cloud Storage facility where I can store useful datasets and trained models which can directly by accessed by API on the fly. Review collected by and hosted on G2.com.

What do you dislike about BigML?

bigML is a great platform for developing machine learning based projects. I am using it from a long time, honestly no dislikes. Review collected by and hosted on G2.com.

Current UserValidated ReviewerIncentivizedSource: G2 invite

Verified User in Computer Software

Small-Business (50 or fewer emp.)

11/30/2017

"Great for lightweight data science tools"

4.5/5

What do you like best about BigML?

- Simple set up to get data loaded

- Easy to set target variables

- Easy to ignore variables Review collected by and hosted on G2.com.

What do you dislike about BigML?

- Automatically creates date variables unnecessarily

- Takes a bit of time to understand how to configure the various models

- Processing concurrent threads is limited based on your tiers Review collected by and hosted on G2.com.

Recommendations to others considering BigML:

There are many tools that have similar value propositions. This is a tool not meant for everyone, but most likely a business user who has a solid understanding of technical data science. If you do not have a background in data science, first take a crash course or considering purchasing a book to give more context on how to leverage data science methodologies. Review collected by and hosted on G2.com.

What problems is BigML solving and how is that benefiting you?

Generally, we try to solve for objectives of both good and bad results (customer acquisition versus churn). By leveraging some machine learning out of the box, we can still get the majority of our insights without having to hire external consultants or a full time resource. Review collected by and hosted on G2.com.

Validated ReviewerIncentivizedSource: G2 invite

Purav A.

Assistant Project Manager

Computer Software

Small-Business (50 or fewer emp.)

11/2/2017

"BigML - A Machine Learning Library"

5/5

What do you like best about BigML?

- Cloud Storage for ML models.

- Provides a wide range of datasets for classification to clustering models.

- API is easy to use. Review collected by and hosted on G2.com.

What do you dislike about BigML?

- No offline support.

- It is complex at some extent, a better option would be scikit-learn: http://scikit-learn.org/ for beginners. Review collected by and hosted on G2.com.

Recommendations to others considering BigML:

There are a lot of datasets that you can easily use to train your models. You can also directly use the trained models through API. Review collected by and hosted on G2.com.

What problems is BigML solving and how is that benefiting you?

- Using as a cloud repository for all of our trained models.

- Developing projects with easy and simple-to-use API. Review collected by and hosted on G2.com.