baikal vs Google Maps
Overview
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CLI (Node.js)
Manual
Detailed Comparison
Create rich applications and stunning visualisations of your data, leveraging the comprehensiveness, accuracy, and usability of Google Maps and a modern web platform that scales as you grow. | It is a graph-based, functional API for building complex machine learning pipelines of objects that implement the scikit-learn API. It is mostly inspired on the excellent Keras API for Deep Learning, and borrows a few concepts from the TensorFlow framework and the (perhaps lesser known) graphkit package. It aims to provide an API that allows to build complex, non-linear machine learning pipelines. |
Maps Image APIs;Places API;Web Services;Google Earth API;Maps API Licensing;Google Maps API for Work
| Build non-linear pipelines effortlessly;
Handle multiple inputs and outputs;
Add steps that operate on targets as part of the pipeline;
Nest pipelines;
Use prediction probabilities (or any other kind of output) as inputs to other steps in the pipeline;
Query intermediate outputs, easing debugging;
Freeze steps that do not require fitting;
Define and add custom steps easily;
Plot pipelines |
Statistics | |
GitHub Stars - | GitHub Stars 590 |
GitHub Forks - | GitHub Forks 30 |
Stacks 42.5K | Stacks 4 |
Followers 29.8K | Followers 11 |
Votes 568 | Votes 0 |
Pros & Cons | |
Pros
Cons
| No community feedback yet |
Integrations | |
| No integrations available | |
What are some alternatives to Google Maps, baikal?
Mapbox
We make it possible to pin travel spots on Pinterest, find restaurants on Foursquare, and visualize data on GitHub.
Leaflet
Leaflet is an open source JavaScript library for mobile-friendly interactive maps. It is developed by Vladimir Agafonkin of MapBox with a team of dedicated contributors. Weighing just about 30 KB of gzipped JS code, it has all the features most developers ever need for online maps.
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.
OpenStreetMap
OpenStreetMap is built by a community of mappers that contribute and maintain data about roads, trails, cafés, railway stations, and much more, all over the world.
OpenLayers
An opensource javascript library to load, display and render maps from multiple sources on web pages.
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/
ArcGIS
It is a geographic information system for working with maps and geographic information. It is used for creating and using maps, compiling geographic data, analyzing mapped information, sharing and much more.
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.
