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  4. Machine Learning As A Service
  5. Kaggle vs TrueFoundry

Kaggle vs TrueFoundry

OverviewComparisonAlternatives

Overview

TrueFoundry
TrueFoundry
Stacks1
Followers1
Votes0
Kaggle
Kaggle
Stacks10
Followers7
Votes0

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Detailed Comparison

TrueFoundry
TrueFoundry
Kaggle
Kaggle

It is a platform that makes it really easy to build, track and deploy models. It is deployed on a cluster on your own cloud so that the data never leaves your environment and you don't incur any data egress costs.

Machine learners share, stress test, and stay up-to-date on all the latest ML techniques and technologies. Discover a huge repository of community-published models, data & code for your next project.

10x faster deployments; Train track and deploy your models; LLM deployment and fine-tuning made easy; Cost savings upto 70%
Find all the resources and knowledge needed for your next real-world ML project; High-quality public datasets. Everything from avocado prices to video game sales; Public notebooks and access to a powerful notebook environment with no cost GPUs & TPUs; Pre-trained, ready-to-deploy ML models; Build your ML skills in a supportive and helpful community
Statistics
Stacks
1
Stacks
10
Followers
1
Followers
7
Votes
0
Votes
0
Integrations
Kubernetes
Kubernetes
Amazon EKS
Amazon EKS
Docker
Docker
GitLab
GitLab
Amazon S3
Amazon S3
Microsoft Azure
Microsoft Azure
GitHub
GitHub
Google Cloud Platform
Google Cloud Platform
Jupyter
Jupyter
Python
Python

What are some alternatives to TrueFoundry, Kaggle?

Pandas

Pandas

Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more.

NanoNets

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.

NumPy

NumPy

Besides its obvious scientific uses, NumPy can also be used as an efficient multi-dimensional container of generic data. Arbitrary data-types can be defined. This allows NumPy to seamlessly and speedily integrate with a wide variety of databases.

Inferrd

Inferrd

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.

PyXLL

PyXLL

Integrate Python into Microsoft Excel. Use Excel as your user-facing front-end with calculations, business logic and data access powered by Python. Works with all 3rd party and open source Python packages. No need to write any VBA!

GraphLab Create

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.

BigML

BigML

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.

SAM 3D

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

Tinker

Is a training API for researchers and developers.

Vexub

Vexub

Create high-quality videos in seconds with Vexub’s AI generator, turning your text or audio into ready-to-publish content for TikTok, YouTube Shorts, and other short-form platforms

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