PyCaret
open source, low-code machine learning library in Python.
Some of the top features or benefits of PyCaret are: Ease of Use, Low-Code, Comprehensive Preprocessing, Model Library, Integration, and Automated Hyperparameter Tuning. You can visit the info page to learn more.
PyCaret Alternatives & Competitors
The best PyCaret alternatives based on verified products, community votes, reviews and other factors.
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Open-Source Alternatives.
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/tensorflow-alternativesTensorFlow 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.
Key TensorFlow features:
Comprehensive Ecosystem Community and Support Flexibility Integrations
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/pytorch-alternativesOpen source deep learning platform that provides a seamless path from research prototyping to...
Key PyTorch features:
Dynamic Computation Graph Pythonic Nature Strong Community Support Flexibility and Control
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Visit websiteDiscover Electe, our data analytics platform dedicated to SMEs. Don't let your data go unused, take your business into the future!
Key Electe features:
Connect your Data Analyze the Data Generate custom reports
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/deeplearning4j-alternativesDeeplearning4j is an open-source, distributed deep-learning library written for Java and Scala.
Key Deeplearning4j features:
Java Integration Scalability Commercial Support Compatibility with Hardware
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/scikit-learn-alternativesscikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
Key Scikit-learn features:
Ease of Use Extensive Documentation and Community Support Integration with Other Libraries Variety of Algorithms
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/keras-alternativesKeras is a minimalist, modular neural networks library, written in Python and capable of running on top of either TensorFlow or Theano.
Key Keras features:
User-Friendly Modularity Pre-trained Models Integration with TensorFlow
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/mlpack-alternativesmlpack is a scalable machine learning library, written in C++.
Key mlpack features:
Performance Open Source Ease of Use Comprehensive Documentation
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/pandas-alternativesPandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
Key Pandas features:
Data Wrangling Flexible Data Structures Integration with Other Libraries Performance with Data Size
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/catboost-alternativesCatBoost - state-of-the-art open-source gradient boosting library with categorical features support, https://catboost.yandex/ #catboost.
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/js-torch-alternativesJS-Torch is a Deep Learning JavaScript library built from scratch, to closely follow PyTorch's syntax.
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/darknet-alternatives
Darknet is an open source neural network framework written in C and CUDA.
Key Darknet features:
Open Source Ease of Use Good Performance YOLO Integration
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/orange-alternativesMachine learning for novice and experts.
Key Orange features:
User-Friendly Interface Open Source Comprehensive Data Visualization Extensive Add-Ons
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/opencv-alternativesOpenCV is the world's biggest computer vision library.
Key OpenCV features:
Comprehensive Library Cross-Platform Compatibility Open Source Large Community Support
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/openai-universe-alternativesPlatform for measuring and training AI agents.
Key OpenAI Universe features:
Comprehensive Environment Suite Rich Learning Scenarios Integration with OpenAI Gym Open Source
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