ProxyCompass
Deeplearning4j
TensorFlow
Keras
PyTorch
Darknet
Scikit-learn
PyCaret
OpenCV
TFlearn
Keras
Clarifai
DeepPy
Microsoft Cognitive Toolkit (Formerly CNTK)
TensorFlow
Merlin
Knet
Deeplearning4j| Categories |
|
|---|---|
| Website | deeplearning4j.org |
| Details $ | - |
TFlearn| Categories |
|
|---|---|
| Website | tflearn.org |
| Details $ |
Based on our record, Deeplearning4j should be more popular than TFlearn. It has been mentiond 4 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.
While KotlinDL seems to be a good solution by Jetbrains, I would personally stick to Java frameworks like DL4J for a better community support and likely more features. Source: over 2 years ago
Would recommend taking a look at dl4j: https://deeplearning4j.org. Source: almost 3 years ago
We use DeepLearning4j in this chapter because it is written in Java and easy to use with Clojure. In a later chapter we will use the Clojure library libpython-clj to access other deep learning-based tools like the Hugging Face Transformer models for question answering systems as well as the spaCy Python library for NLP. Source: almost 3 years ago
FastAPI. Or even simpler: DL4J, to be used in Java when we need to communicate with the rest of the applications in real time. Source: about 3 years ago
TFLearn – Deep learning library featuring a higher-level API for TensorFlow. - Source: dev.to / over 1 year 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
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.
Keras - Keras is a minimalist, modular neural networks library, written in Python and capable of running on top of either TensorFlow or Theano.
Clarifai - The World's AI
PyTorch - Open source deep learning platform that provides a seamless path from research prototyping to...
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.
Darknet - Darknet is an open source neural network framework written in C and CUDA.