Datature
Colornet
DALL-E
Quick Draw Game
MakeML
TensorFire
Machine Learning Playground
Neuton.AI
PyTorch
TensorFlow
Keras
Scikit-learn
OpenCV
CUDA
NumPy
Pandas
Datature PyTorchBased on our record, PyTorch seems to be a lot more popular than Datature. While we know about 106 links to PyTorch, we've tracked only 7 mentions of Datature. 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.
Of course, you can write your own code, in that case, think of it as an interactive matplotlib then! Also, it helps to mention we run a startup Datature, that is a no-code MLOps platform, hence explaining why we are focusing on removing the coding portion of this process :P. Source: almost 3 years ago
A while ago, we announced here that we built Datature and a bunch of users gave feedback and even built MaskRCNN models on our platform! However, we were sending collab updates back and forth - it was a mess. Hence we made Portal for any TensorFlow users to load TF2.0 models (any models off TF2 Model Hub works) and inspect your model visually on your dataset. Source: almost 3 years ago
If you'd like to train a tensorflow object detection model, you can check out https://datature.io - theres about 30 different models you can select from and you can add augmentation to your pipeline. Source: about 3 years ago
If you will be training an object detection model at the end, you can check out https://datature.io - you can annotate your data in browser (no installation) and train an object detection model + deploy when you are done for free! Source: about 3 years ago
Feel free to try it out at https://datature.io - additionally, we are always looking out for feedback and feature requests. We are working more MLOps feature to support teams, so let us know of your thoughts :). Source: about 3 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 / about 1 month ago
*My post explains Dot, Matrix and Element-wise multiplication in PyTorch. - Source: dev.to / 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 / 3 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 / 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 / 2 months ago
Colornet - Neural Network to colorize grayscale images
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.
DALL-E - Creating images from text, from Open AI
Keras - Keras is a minimalist, modular neural networks library, written in Python and capable of running on top of either TensorFlow or Theano.
Quick Draw Game - Can a neural network learn to recognize doodles?
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
