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machine-learning in Python VS Datadog

Compare machine-learning in Python VS Datadog and see what are their differences

machine-learning in Python logo machine-learning in Python

Do you want to do machine learning using Python, but you’re having trouble getting started? In this post, you will complete your first machine learning project using Python.

Datadog logo 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.
  • machine-learning in Python Landing page
    Landing page //
    2020-01-13
  • Datadog Landing page
    Landing page //
    2023-10-05

Datadog is a monitoring and analytics platform for cloud-scale application infrastructure. Combining metrics from servers, databases, and applications, Datadog delivers sophisticated, actionable alerts, and provides real-time visibility of your entire infrastructure. Datadog includes 100+ vendor-supported, prebuilt integrations and monitors hundreds of thousands of hosts.

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Datadog Review & Walkthrough

More videos:

  • Review - DataDog: What it is and where its going
  • Review - Datadog: 2-Minute Tour

Category Popularity

0-100% (relative to machine-learning in Python and Datadog)
Data Science And Machine Learning
Monitoring Tools
0 0%
100% 100
Data Dashboard
100 100%
0% 0
Log Management
0 0%
100% 100

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Reviews

These are some of the external sources and on-site user reviews we've used to compare machine-learning in Python and Datadog

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Datadog Reviews

Top 10 Grafana Alternatives in 2024
While all Grafana alternatives do not offer pricing transparency, go for a flexible pricing structure that fits your budget. Tools like Datadog offer pricing based on data volume or monitoring scope, while Middleware offers a flexible pay-as-you-go pricing structure.
Source: middleware.io
Top 11 Grafana Alternatives & Competitors [2024]
Open Source vs. Proprietary: Determine whether an open-source solution like SigNoz or a proprietary one like Datadog better aligns with your requirements and budget. Open-source tools often offer more customization and community support, while proprietary tools may provide more comprehensive out-of-the-box features and dedicated customer service. At SigNoz, we offer both...
Source: signoz.io
10 Best Grafana Alternatives [2023 Comparison]
Datadog is a massive tool that offers a lot of features and solutions, including log management. But before we dive too deep, please note that Datadog is expensive. It absolutely is not for anyone other than large-budgeted corporations. Just take a look at what people are saying on X.
Source: sematext.com
5 Best DevSecOps Tools in 2023
There are many platforms that can be utilized for monitoring and alerting. Some examples are New Relic, Datadog, AWS CloudWatch, Sentry, Dynatrace, and others. Again, these providers each have pros and cons related to pricing, offering, ad vendor lock-in. So research the options to see what may possibly be best for a given situation.
Best API Monitoring and Observability Tools in 2023
Datadog’s API monitoring lets you automate site availability monitoring and reduce average time it takes to get to the cause. It also allows you to validate all the layers of your systems (from HTTP to DNS) from multiple geolocations, letting you focus on areas that are vital to your business by creating custom locations.
Source: apitoolkit.io

Social recommendations and mentions

machine-learning in Python might be a bit more popular than Datadog. We know about 7 links to it since March 2021 and only 5 links to Datadog. 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.

machine-learning in Python mentions (7)

  • Data science and cybersecurity with python project
    After that you should probably look at some very basic ML tutorials. I just googled it, I have no idea if this is good https://machinelearningmastery.com/machine-learning-in-python-step-by-step/. Source: over 1 year ago
  • Ask HN: How can I learn ML in 6 months as a teenager?
    Few different approaches based on search engine 'ml with python': Work though use cases / examples : https://www.databricks.com/resources/ebook/big-book-of-machine-learning-use-cases On-line class(es) / step by step projects: * https://bootcamp-sl.discover.online.purdue.edu/ai-machine-learning-certification-course * https://www.w3schools.com/python/python_ml_getting_started.asp *... - Source: Hacker News / over 1 year ago
  • Are these CS courses enough CS knowledge for ML engineer?
    MLE: ALL OF THE ABOVE (this is important - pure machine learning skills generally won’t make you hireable unless you’re doing a PhD and/or are a genius) Plus: 1. https://machinelearningmastery.com/machine-learning-in-python-step-by-step/ 2. https://www.coursera.org/learn/machine-learning 3. https://www.3blue1brown.com/topics/neural-networks. Source: about 2 years ago
  • how to do i train an AI
    Have you seen this? https://machinelearningmastery.com/machine-learning-in-python-step-by-step/. Source: over 2 years ago
  • Python Data Science Project Ideas (+References)
    Machine learning models Fine-tune existing machine learning models for improved accuracy, or create your own custom models. - Source: dev.to / over 2 years ago
View more

Datadog mentions (5)

  • Send the logs of your Shuttle-powered backend to Datadog
    Ideally, if we had access to the underlying infrastructure, we could probably install the Datadog Agent and configure it to send our logs directly to Datadog, or even use AWS Lambda functions or Azure Event Hub + Azure Functions in case we were facing some specific cloud scenarios. - Source: dev.to / 9 months ago
  • I wanted a self hosted alternative to Atlassian status page so I build my own application !
    Currently supported : Datadog, Jenkins, DNS, HTTP. Source: over 1 year ago
  • Datadog on Kubernetes: Avoiding Common Pitfalls
    Datadog is a powerful monitoring and security platform that gives you visibility into end-to-end traces, application metrics, logs, and infrastructure. While Datadog has great documentation on their Kubernetes integration, we've observed that there's some missed nuance that leads to common pitfalls. - Source: dev.to / almost 3 years ago
  • Post-DockerCon spam
    .. Is to see you email address being silently distributed to every single company that I've watched a talk from. And now suddenly get several promotional spam emails per day from some 4-5 different domains like instana.com, datadoghq.com, snyk.io, cockroachlabs.com (some of them send even multiple emails per day!). Source: about 3 years ago
  • Never write a UserService again
    We're commonly doing this with logging, using services such as Loggly or DataDog. We're using managed databases, be it on AWS, Heroku or database-vendor-specific solutions. We're storing binaries on S3. Externalising user authentication and authorization might be a good candidate as well. - Source: dev.to / about 3 years ago

What are some alternatives?

When comparing machine-learning in Python and Datadog, you can also consider the following products

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

Zabbix - Track, record, alert and visualize performance and availability of IT resources

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

Dynatrace - Cloud-based quality testing, performance monitoring and analytics for mobile apps and websites. Get started with Keynote today!

Google Cloud TPU - Custom-built for machine learning workloads, Cloud TPUs accelerate training and inference at scale.

NewRelic - New Relic is a Software Analytics company that makes sense of billions of metrics across millions of apps. We help the people who build modern software understand the stories their data is trying to tell them.