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BigML VS Coralogix

Compare BigML VS Coralogix and see what are their differences

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Contents:
  1. » Base Details
  2. » Videos
  3. » Reviews
  4. » Alternatives

BigML logo BigML

BigML's goal is to create a machine learning service extremely easy to use and seamless to integrate.

Coralogix logo Coralogix

Coralogix is a machine learning powered log analytics solution aimed to solve the problem of unmanageable log data.
  • BigML Landing page
    Landing page //
    2022-10-08
  • Coralogix Landing page
    Landing page //
    2023-10-14

BigML videos

+ Add

BigML is Machine Learning for Everyone

More videos:

  • Review - BigML Spring 2016 Webinar - WhizzML!

Coralogix videos

+ Add

Coralogix and BetterHelp [Case Study]

More videos:

  • Review - How Capgemini Solved Multi-Cloud Observability on Heroku with Coralogix
  • Review - Coralogix and Postman [Case Study]

Category Popularity

0-100% (relative to BigML and Coralogix)

BigML

Coralogix

Data Science And Machine Learning
100 100%
Data Science And Machine Learning
0% 0
Customer Support
0 0%
Customer Support
100% 100
Data Science Tools
100 100%
Data Science Tools
0% 0
Network & Admin
0 0%
Network & Admin
100% 100

User comments

Share your experience with using BigML and Coralogix. For example, how are they different and which one is better?
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Social recommendations and mentions

Coralogix might be a bit more popular than BigML. We know about 2 links to it since March 2021 and only 2 links to BigML. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

BigML mentions (2)

  • Free for dev - list of software (SaaS, PaaS, IaaS, etc.)
    Bigml.com — Hosted machine learning algorithms. Unlimited free tasks for development, limit of 16 MB data/task. - Source: dev.to / almost 3 years ago
  • Theory: The price action was intentionally manipulated to prevent any AI from being able to predict it. First time this model shows as flat. Forever.
    They know the website is bigml.com it's possible they have many magnitudes better algorithms to predict this shit. And it's also possible they paid some quants to come up with price action that just completely fucks with BigML's algorithm entirely to make it look flat. Source: about 3 years ago

Coralogix mentions (2)

  • I can't recommend serious use of an all-in-one local Grafana Loki setup
    In defense of Grafana Loki, it's awesome... If you have a lot of information about your telemetry data up front - i.e volumes, use cases, how you wish to query it etc. A broader solution like Coralogix (https://coralogix.com/) is more appropriate if you're venturing into the unknown and you need more of a data discovery capability. The problem with most of THESE "all in one" platforms is they tried flexibility and... - Source: Hacker News / about 1 year ago
  • Coralogix is hiring a remote Rust developer! (not blockchain!)
    We, coralogix.com, are looking for a Rust engineer with some experience of database engineering. Source: about 2 years ago

What are some alternatives?

When comparing BigML and Coralogix, you can also consider the following products

RapidMiner - RapidMiner is a software platform for data science teams that unites data prep, machine learning, and predictive model deployment.

Datadog - See metrics from all of your apps, tools & services in one place with Datadog's cloud monitoring as a service solution. Try it for free.

Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.

Noction Flow Analyzer (NFA) - Powerful, Feature-rich, Affordable in-depth traffic analysis system, built with network engineers in mind.

Qubole - Qubole delivers a self-service platform for big aata analytics built on Amazon, Microsoft and Google Clouds.

SolarWinds Orion Platform - SolarWinds Orion Platform is an infrastructure monitoring and management solution that has been designed to streamline and manage the composite and physically dispersed IT infrastructure.

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