PaddlePaddle
Keras
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| PaddlePaddle | Keras | |
|---|---|---|
| 2 | 48 | |
| 18,198 | 55,214 | |
| 1.9% | 0.7% | |
| 10.0 | 9.9 | |
| 5 days ago | 5 days ago | |
| C++ | Python | |
| Apache License 2.0 | Apache License 2.0 |
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PaddlePaddle
Keras
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Should you shuffle the input for a word2vec negative sampling model before or after assigning negative context pairs for each target word?
I may have a few trust issues with the shuffle argument of keras' model.fit(), after experiencing this bug regarding shuffle='batch' first hand.
- Reciclaje 3.0
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Has anyone ever experienced this ? details in the comments.
it seems like other people have had this issue like another user mentioned when using dropout or BN (https://github.com/keras-team/keras/issues/6977) , the model does use dropout so that maybe it .
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How to define max_queue_size, workers and use_multiprocessing in keras fit_generator()?
Detailed explanation of model.fit_generator() parameters: queue size, workers and use_multiprocessing
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Negative dimension size caused by subtracting 3 from 1 for 'Conv2D'
I'm using Keras with Tensorflow as backend , here is my code:
- Python or javascript?
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How to get reproducible results in keras
Install Keras (http://keras.io/)
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20+ Free Tools & Resources for Machine Learning
Keras Keras is an API for neural networks that helps doing quick research.
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Installing Python3 in Linux
According to IBM, Artificial Intelligence (AI) is technology that instructs computers to mimic the human mind in decision-making and problem-solving. Machine Learning (ML) is a subset of AI that consist of procedures that leverage on mathematical data models and algorithms to make predictions. Python implements ML and AI with generally fewer lines of code and pre-built libraries and being a scientific language also comes in support of these technologies. Some of the libraries used in AI and ML include: Tensorflow, Scikit-Learn, Numpy, Keras, Theano
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How to build your own chatbot NLP engine
At the core of the Xatkit NLU engine we have a Keras/Tensorflow model.
What are some alternatives?
tensorflow - An Open Source Machine Learning Framework for Everyone
MLP Classifier - A handwritten multilayer perceptron classifer using numpy.
scikit-learn - scikit-learn: machine learning in Python
xgboost - Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow
TFLearn - Deep learning library featuring a higher-level API for TensorFlow.
Prophet - Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
PyTorch-NLP - Basic Utilities for PyTorch Natural Language Processing (NLP)
pytorch-lightning - The lightweight PyTorch wrapper for high-performance AI research. Scale your models, not the boilerplate.
Pandas - Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
skflow - Simplified interface for TensorFlow (mimicking Scikit Learn) for Deep Learning
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration