Swift Playgrounds
CodeMonkey
GitHub Codespaces
CodeTasty
StackHive
CloudShell
CodeAbbey
Dirigible
TFlearn
Keras
Clarifai
DeepPy
Microsoft Cognitive Toolkit (Formerly CNTK)
Merlin
Knet
TensorFlow
Swift Playgrounds TFlearnThe 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, TFlearn seems to be more popular. It has been mentiond 2 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.
TFLearn – Deep learning library featuring a higher-level API for TensorFlow. - Source: dev.to / almost 2 years ago
Both the teams in a game are given their individual ID values and are made into vectors. Relevant data like the home and away team, home runs, RBI’s, and walk’s are all taken into account and passed through layers. There’s no need to reinvent the wheel here, there's a multitude of libraries that enable a coder to implement machine learning theories efficiently. In this case we will be using a library called... - Source: dev.to / about 3 years ago
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.
GitHub Codespaces - GItHub Codespaces is a hosted remote coding environment by GitHub based on Visual Studio Codespaces integrated directly for GitHub.
Clarifai - The World's AI
CodeTasty - CodeTasty is a programming platform for developers in the cloud.
DeepPy - DeepPy is a MIT licensed deep learning framework that tries to add a touch of zen to deep learning as it allows for Pythonic programming.
