Software Alternatives & Reviews

Exploratory VS Amazon SageMaker

Compare Exploratory VS Amazon SageMaker and see what are their differences

Exploratory logo Exploratory

Exploratory enables users to understand data by transforming, visualizing, and applying advanced statistics and machine learning algorithms.

Amazon SageMaker logo Amazon SageMaker

Amazon SageMaker provides every developer and data scientist with the ability to build, train, and deploy machine learning models quickly.
  • Exploratory Landing page
    Landing page //
    2023-09-12
  • Amazon SageMaker Landing page
    Landing page //
    2023-03-15

Exploratory videos

1.3 Exploratory, Descriptive and Explanatory Nature Of Research

More videos:

  • Review - Exploratory Process Content Review
  • Review - Reviewing Your Data Science Projects - Episode 1 (Exploratory Analysis)

Amazon SageMaker videos

Build, Train and Deploy Machine Learning Models on AWS with Amazon SageMaker - AWS Online Tech Talks

More videos:

  • Review - An overview of Amazon SageMaker (November 2017)

Category Popularity

0-100% (relative to Exploratory and Amazon SageMaker)
Data Science And Machine Learning
Data Science Tools
100 100%
0% 0
AI
0 0%
100% 100
Python Tools
100 100%
0% 0

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Exploratory and Amazon SageMaker

Exploratory Reviews

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Amazon SageMaker Reviews

7 best Colab alternatives in 2023
Amazon SageMaker Studio is a fully integrated development environment (IDE) for machine learning. It allows users to write code, track experiments, visualize data, and perform debugging and monitoring all within a single, integrated visual interface, making the process of developing, testing, and deploying models much more manageable.
Source: deepnote.com

Social recommendations and mentions

Based on our record, Amazon SageMaker should be more popular than Exploratory. It has been mentiond 35 times since March 2021. 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.

Exploratory mentions (6)

  • Excel Never Dies
    I'm a happy customer of https://exploratory.io/ - it's a very user-friendly interface on top of R and I think you might find it helpful. - Source: Hacker News / over 1 year ago
  • Fast Lane to Learning R
    If the goal here is becoming productive quickly, try https://exploratory.io/ which is a sort of WYSIWYG environment for R that will still let you code by hand if needed. No affiliation, just a happy customer for 2 years. - Source: Hacker News / almost 2 years ago
  • Excel 2.0 – Is there a better visual data model than a grid of cells?
    Give https://exploratory.io/ a look. It's free/cheap. It's a nice easy GUI wrapper for R and just works. I stumbled across it a year ago and now use it daily. - Source: Hacker News / about 2 years ago
  • Why no love for Exploratory Desktop?
    I'm not associated with the company, but I have used their product extensively and recommended it before. Is there a reason people do not recommend Exploratory Desktop compared to something like Tableau? It is free for public use, and can do almost anything Tableau does but faster: https://exploratory.io/. Source: about 2 years ago
  • A Quick Introduction to R
    I've been using https://exploratory.io/ a lot, which is r in a really nice wrapper where you can do everything point and click, by writing code by hand or a mix. - Source: Hacker News / about 2 years ago
View more

Amazon SageMaker mentions (35)

  • Sentiment Analysis with PubNub Functions and HuggingFace
    At this point, probably everyone has heard about OpenAI, GPT-4, Claude or any of the popular Large Language Models (LLMs). However, using these LLMs in a production environment can be expensive or nondeterministic regarding its results. I guess that is the downside of being good at everything; you could be better at performing one specific task. This is where HuggingFace can utilized. HuggingFace provides... - Source: dev.to / 20 days ago
  • Beginning the Journey into ML, AI and GenAI on AWS
    Generative Artificial Intelligence (GenAI) is a type of artificial intelligence that can generate text, images, or other media using generative models. AWS offers a range of services for building and scaling generative AI applications, including Amazon SageMaker, Amazon Rekognition, AWS DeepRacer, and Amazon Forecast. AWS has also invested in developing foundation models (FMs) for generative AI, which are... - Source: dev.to / 3 months ago
  • Technical Architecture for LLMOps
    Amazon and Azure already have much of what you're talking about in AWS SageMaker and Azure MLOps. Source: 11 months ago
  • Are AI fine-tuning tools worth learning and investing?
    And there have been several platforms that help fine-tune pretrained models, such as Google Cloud AutoML and Amazon Sagemaker. These tools are often fairly easy to use, but they come at a cost. They can be expensive, depending on the size of your dataset. Another option is Finetuner+, that also fine-tunes like AutoML and Sagemaker. The big advantage is that you don't need to transfer your data to other GPUs,... Source: almost 1 year ago
  • Live object recognition system using Kinesis and SageMaker
    In this blog, you will see how to ingest audio/video feeds from any live recording camera into the AWS Kinesis Video Stream and apply various machine learning algorithms on the video stream to analyze these video feeds using Amazon SageMaker. We'll also use a few other services like Lambda, S3, EC2, IAM, ECS, CloudFormation, ECR, CloudWatch, etc. To power our model. Source: about 1 year ago
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What are some alternatives?

When comparing Exploratory and Amazon SageMaker, 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.

TensorFlow - TensorFlow is an open-source machine learning framework designed and published by Google. It tracks data flow graphs over time. Nodes in the data flow graphs represent machine learning algorithms. Read more about TensorFlow.

Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.

IBM Watson Studio - Learn more about Watson Studio. Increase productivity by giving your team a single environment to work with the best of open source and IBM software, to build and deploy an AI solution.

NumPy - NumPy is the fundamental package for scientific computing with Python

Azure Machine Learning Studio - Azure Machine Learning Studio is a GUI-based integrated development environment for constructing and operationalizing Machine Learning workflow on Azure.