Swift Playgrounds
GitHub Codespaces
CodeMonkey
CodeTasty
StackHive
CloudShell
CodeAbbey
Dirigible
PyTorch
TensorFlow
Keras
Scikit-learn
OpenCV
CUDA
NumPy
Pandas
Swift Playgrounds PyTorchThe lowest available rating score is 1, but if there were a zero, I would rate this program a zero. There are no pros to this programming course. The lessons are so brief that I cannot understand them. Before I gave up for good on this programming course, I was writing tons of messages to people on Youtube asking them to explain things to me, and I hated the constant hassle of having to write online messages asking for explanations for the simplest of things that the lessons did not explain. This programming course is NOT a do-it-yourself training course by any means --- and it should not be used by schoolteachers as student homework assignments, as I recently advised a 13-year-old who was having trouble with the lessons and nothing was being helpful to him. This training course should be accompanied not by brief and intelligible on-screen lessons, but it should be accompanied by a detailed high school-style textbook complete with images. By the way, I have Asperger's syndrome, I have all kinds of problems with learning and with executing tasks, and I cannot participate in gainful employment in ANY profession for this reason.
Based on our record, PyTorch seems to be more popular. It has been mentiond 106 times since March 2021. 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.
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
GitHub Codespaces - GItHub Codespaces is a hosted remote coding environment by GitHub based on Visual Studio Codespaces integrated directly for GitHub.
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.
CodeMonkey - Learn to code. Eat Bananas. Save the World.
Keras - Keras is a minimalist, modular neural networks library, written in Python and capable of running on top of either TensorFlow or Theano.
CodeTasty - CodeTasty is a programming platform for developers in the cloud.
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.