BigML vs Inferrd

Overview

BigML

Stacks14

Followers29

Votes1

Inferrd

Stacks2

Followers11

Votes10

BigML vs Inferrd: What are the differences?

BigML: Machine Learning, made simple. Predictive analytics for big data and not-so-big data. BigML provides a hosted machine learning platform for advanced analytics. Through BigML's intuitive interface and/or its open API and bindings in several languages, analysts, data scientists and developers alike can quickly build fully actionable predictive models and clusters that can easily be incorporated into related applications and services; Inferrd: *Deploy ML Models with a Simple Drag and Drop *. It is the easiest way to deploy Machine Learning models. Start deploying Tensorflow, Scikit, Keras and spaCy straight from your notebook with just one extra line.

BigML and Inferrd can be categorized as "Machine Learning as a Service" tools.

Some of the features offered by BigML are:

REST API
bindings in Pyton, Java, Ruby, node.js, C#, Clojure, PHP, and more
several algorithms, including categorical & regression decision trees, ensembles of trees (random decision forest), cluster analysis and more

On the other hand, Inferrd provides the following key features:

Machine Learning practioners don't need to wait for engineering to deploy their models anymore
No need to invest in expensive infrastructure and tooling. Inferrd starts at $14, batteries included
Built with security in mind. Your models are protected using state-of-the-art encryption at rest.

🔥 Trending in Text & Language Models on StackShare

Clever AI Humanizer

AI Text Language Models

Clever AI Humanizer

Try it View Docs Alternatives

Try

0

1

Detailed Comparison

BigML	Inferrd
BigML provides a hosted machine learning platform for advanced analytics. Through BigML's intuitive interface and/or its open API and bindings in several languages, analysts, data scientists and developers alike can quickly build fully actionable predictive models and clusters that can easily be incorporated into related applications and services.	It is the easiest way to deploy Machine Learning models. Start deploying Tensorflow, Scikit, Keras and spaCy straight from your notebook with just one extra line.
REST API; bindings in Pyton, Java, Ruby, node.js, C#, Clojure, PHP, and more; several algorithms, including categorical & regression decision trees, ensembles of trees (random decision forest), cluster analysis and more; models are fully actionable -- translated into code that can be cut/paste for local utilization; PredictServer (and Amazon AMI) can be used for real-time or large batch predictions; models can be shared privately or publicly (for free or for a fee set by the developer)	Machine Learning practioners don't need to wait for engineering to deploy their models anymore; No need to invest in expensive infrastructure and tooling. Inferrd starts at $14, batteries included; Built with security in mind. Your models are protected using state-of-the-art encryption at rest.
Statistics
Stacks 14	Stacks 2
Followers 29	Followers 11
Votes 1	Votes 10
Pros & Cons
Pros 1 Ease of use, great REST API and ML workflow automation	Pros 3 Easy to use 2 Very quick response time 2 Fast 2 Secure 1 Fair pricing
Integrations
No integrations available	TensorFlow SpaCy Keras scikit-learn

What are some alternatives to BigML, Inferrd?

NanoNets

Build a custom machine learning model without expertise or large amount of data. Just go to nanonets, upload images, wait for few minutes and integrate nanonets API to your application.

GraphLab Create

Building an intelligent, predictive application involves iterating over multiple steps: cleaning the data, developing features, training a model, and creating and maintaining a predictive service. GraphLab Create does all of this in one platform. It is easy to use, fast, and powerful.

SAM 3D

Explore SAM 3D to reconstruct 3D objects, people and scenes from a single image. Build 3D assets faster with SAM 3D Objects and SAM 3D Body.

Tinker

Is a training API for researchers and developers.

AI Video Generator

Create AI videos at 60¢ each - 50% cheaper than Veo3, faster than HeyGen. Get 200 free credits, no subscription required. PayPal supported. Start in under 2 minutes.

Sportlingo

AI-powered sports analytics and skill assessment API that enables apps and platforms to deliver personalized training, drills, and performance insights.

Amazon SageMaker

A fully-managed service that enables developers and data scientists to quickly and easily build, train, and deploy machine learning models at any scale.

Azure Machine Learning

Azure Machine Learning is a fully-managed cloud service that enables data scientists and developers to efficiently embed predictive analytics into their applications, helping organizations use massive data sets and bring all the benefits of the cloud to machine learning.

Amazon Machine Learning

This new AWS service helps you to use all of that data you’ve been collecting to improve the quality of your decisions. You can build and fine-tune predictive models using large amounts of data, and then use Amazon Machine Learning to make predictions (in batch mode or in real-time) at scale. You can benefit from machine learning even if you don’t have an advanced degree in statistics or the desire to setup, run, and maintain your own processing and storage infrastructure.