Backprop vs Streamlit
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It is the app framework specifically for Machine Learning and Data Science teams. You can rapidly build the tools you need. Build apps in a dozen lines of Python with a simple API. | It is an API/platform that makes enhancing software with machine learning simple. With powerful out-of-the-box models, easy custom uploads, and scalable infrastructure it has everything you need. |
Free and open source; Build apps in a dozen lines of Python with a simple API; No callbacks; No hidden state; Works with TensorFlow, Keras, PyTorch, Pandas, Numpy, Matplotlib, Seaborn, Altair, Plotly, Bokeh, Vega-Lite, and more
| Conversational question answering in English;
Text Classification in 100+ languages;
Image Classification;
Text Vectorisation in 50+ languages;
Image Vectorisation;
Summarisation in English;
Emotion detection in English;
Text Generation |
Statistics | |
GitHub Stars 42.1K | GitHub Stars 242 |
GitHub Forks 3.9K | GitHub Forks 11 |
Stacks 404 | Stacks 0 |
Followers 407 | Followers 4 |
Votes 12 | Votes 0 |
Pros & Cons | |
Pros
| No community feedback yet |
Integrations | |
| No integrations available | |
What are some alternatives to Streamlit, Backprop?
TensorFlow
TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API.
scikit-learn
scikit-learn is a Python module for machine learning built on top of SciPy and distributed under the 3-Clause BSD license.
PyTorch
PyTorch is not a Python binding into a monolothic C++ framework. It is built to be deeply integrated into Python. You can use it naturally like you would use numpy / scipy / scikit-learn etc.
Keras
Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on TensorFlow or Theano. https://keras.io/
Kubeflow
The Kubeflow project is dedicated to making Machine Learning on Kubernetes easy, portable and scalable by providing a straightforward way for spinning up best of breed OSS solutions.
TensorFlow.js
Use flexible and intuitive APIs to build and train models from scratch using the low-level JavaScript linear algebra library or the high-level layers API
Polyaxon
An enterprise-grade open source platform for building, training, and monitoring large scale deep learning applications.
MLflow
MLflow is an open source platform for managing the end-to-end machine learning lifecycle.
H2O
H2O.ai is the maker behind H2O, the leading open source machine learning platform for smarter applications and data products. H2O operationalizes data science by developing and deploying algorithms and models for R, Python and the Sparkling Water API for Spark.
PredictionIO
PredictionIO is an open source machine learning server for software developers to create predictive features, such as personalization, recommendation and content discovery.
