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Based on our record, PyTorch seems to be a lot more popular than MapWithAI. While we know about 106 links to PyTorch, we've tracked only 5 mentions of MapWithAI. 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.
I'm not fan of Facebook but what about React? Also if we are talking about "AI": https://mapwith.ai. - Source: Hacker News / about 1 year ago
The day iD adds a simple way to measure width on aerial, it will get mapped everywhere. I exaggerate, but OSM is a work in progress and better tools means better maps. Hell, RapID can probably eventually offer values automatically. If only JOSM didn't look like accounting software, people would micromap there more too. Source: almost 2 years ago
I'm a novice contributor, primarily using StreetComplete and the online editor. From some of what I've read, they've been burned by some imports in the past and are gunshy with mass imports. > Why are we still drawing house by house when many cities offer this data freely? It's not perfect, but there are some AI assistants which make this less tedious. https://mapwith.ai/#13/-18.221/35.1573/0/55b (note: I believe... - Source: Hacker News / over 2 years ago
I used Map With AI to add some of the buildings because it allows you to import from the LINZ house database (Not AI!). Source: over 2 years ago
StreetComplete is an easy way to start contributing to OSM without needing to know anything about how OSM stores data. Another great program to contribute to OSM is MapWithAI. It uses computer vision to identify the shapes of buildings and roads, so that you can add them to the map with one click. The AI assistance considerably speeds up the process of adding items to the map. MapWithAI is integrated with the... - Source: Hacker News / over 2 years ago
TensorFlow, developed by Google, and PyTorch, developed by Facebook, are two of the most popular frameworks for building and training complex machine learning models. TensorFlow is known for its flexibility and robust scalability, making it suitable for both research prototypes and production deployments. PyTorch is praised for its ease of use, simplicity, and dynamic computational graph that allows for more... - Source: dev.to / 13 days ago
*My post explains Dot, Matrix and Element-wise multiplication in PyTorch. - Source: dev.to / about 2 months ago
Import torch # we use PyTorch: https://pytorch.org Data = torch.tensor(encode(text), dtype=torch.long) Print(data.shape, data.dtype) Print(data[:1000]) # the 1000 characters we looked at earlier will to the GPT look like this. - Source: dev.to / 2 months ago
AI's Open Embrace Artificial intelligence (AI) and machine learning (ML) are increasingly leveraging open-source frameworks like TensorFlow [https://www.tensorflow.org/] and PyTorch [https://pytorch.org/]. This democratization of AI tools is driving innovation and lowering entry barriers across industries. - Source: dev.to / about 2 months ago
Which label applies to a tool sometimes depends on what you do with it. For example, PyTorch or TensorFlow can be called a library, a toolkit, or a machine-learning framework. - Source: dev.to / about 2 months ago
Mapiful - Create & order custom printed maps of your favorite places
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.
Conquer.Earth - Share a map marked with every place you've ever visited
Keras - Keras is a minimalist, modular neural networks library, written in Python and capable of running on top of either TensorFlow or Theano.
TiltMaps - Create map posters of your favorite places & memories.
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.