practical #variational #autoencoders using #Pytorch
and a simpler version using #Keras!
via: @cedeeplearning
https://becominghuman.ai/variational-autoencoders-for-new-fruits-with-keras-and-pytorch-6d0cfc4eeabd
and a simpler version using #Keras!
via: @cedeeplearning
https://becominghuman.ai/variational-autoencoders-for-new-fruits-with-keras-and-pytorch-6d0cfc4eeabd
Medium
Variational AutoEncoders for new fruits with Keras and Pytorch.
There’s two things you typically love being a Data Scientist at FoodPairing: Machine Learning and food (order up for debate…). So when you…
🔻10 Best Machine Learning Frameworks in 2020
1. #TensorFlow
2. Google Cloud ML Learning
3. Apache Mahout
4. Shogun
5. Sci-Kit Learn
6. #PyTorch or TORCH
7. H2O
8. Microsoft Cognitive Toolkit (#CNTK)
9. #Apache MXNet
10. Apple's Core ML
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https://www.cubix.co/blog/best-machine-learning-frameworks-in-2020
📌Via: @cedeeplearning
#deeplearning
#machinelearning
#datascience
1. #TensorFlow
2. Google Cloud ML Learning
3. Apache Mahout
4. Shogun
5. Sci-Kit Learn
6. #PyTorch or TORCH
7. H2O
8. Microsoft Cognitive Toolkit (#CNTK)
9. #Apache MXNet
10. Apple's Core ML
—————————————————
https://www.cubix.co/blog/best-machine-learning-frameworks-in-2020
📌Via: @cedeeplearning
#deeplearning
#machinelearning
#datascience
Cubix
10 Best Machine Learning Frameworks in 2020 | Deep Learning Platforms
ML and Deep Learning platforms are the technology of tomorrow. The guide tells you the 10 best machine learning or deep learning frameworks of 2020
🔹 LSTM for time series prediction
🖊By Roman Orac
🔻Learn how to develop a LSTM neural network with #PyTorch on trading data to predict future prices by mimicking actual values of the time series data.
In this blog post, I am going to train a Long Short Term Memory Neural Network (LSTM) with PyTorch on Bitcoin trading data and use it to predict the price of unseen trading data. I had quite some difficulties with finding intermediate tutorials with a repeatable example of training an #LSTM for time series prediction, so I’ve put together a #Jupyter notebook to help you to get started.
—————————
📌Via: @cedeeplearning
https://www.kdnuggets.com/2020/04/lstm-time-series-prediction.html
#deeplearning #AI #machinelearning
#neuralnetworks #timeseries
🖊By Roman Orac
🔻Learn how to develop a LSTM neural network with #PyTorch on trading data to predict future prices by mimicking actual values of the time series data.
In this blog post, I am going to train a Long Short Term Memory Neural Network (LSTM) with PyTorch on Bitcoin trading data and use it to predict the price of unseen trading data. I had quite some difficulties with finding intermediate tutorials with a repeatable example of training an #LSTM for time series prediction, so I’ve put together a #Jupyter notebook to help you to get started.
—————————
📌Via: @cedeeplearning
https://www.kdnuggets.com/2020/04/lstm-time-series-prediction.html
#deeplearning #AI #machinelearning
#neuralnetworks #timeseries
KDnuggets
LSTM for time series prediction - KDnuggets
Learn how to develop a LSTM neural network with PyTorch on trading data to predict future prices by mimicking actual values of the time series data.
🔻Speeding Up Deep Learning Inference Using TensorRT
📈 This version starts from a #PyTorch model instead of the #ONNX model, upgrades the sample application to use #TensorRT 7, and replaces the ResNet-50 #classification model with UNet, which is a segmentation model.
📈 NVIDIA TensorRT is an SDK for deep learning inference. TensorRT provides APIs and parsers to import trained models from all major deep learning frameworks. It then generates optimized runtime engines deployable in the datacenter as well as in automotive and embedded environments.
🔹Simple TensorRT example
🔻Convert the pretrained image segmentation PyTorch model into ONNX.
🔻Import the ONNX model into TensorRT.
🔻Apply optimizations and generate an engine.
🔻Perform inference on the GPU.
⭕️ DO NOT MISS OUT THIS ARTICLE
—————————
📌Via: @cedeeplearning
📌Other social media: https://linktr.ee/cedeeplearning
link: https://devblogs.nvidia.com/speeding-up-deep-learning-inference-using-tensorrt/
#NVIDIA #deeplearning #neuralnetworks #python
#machinelearning #AI
📈 This version starts from a #PyTorch model instead of the #ONNX model, upgrades the sample application to use #TensorRT 7, and replaces the ResNet-50 #classification model with UNet, which is a segmentation model.
📈 NVIDIA TensorRT is an SDK for deep learning inference. TensorRT provides APIs and parsers to import trained models from all major deep learning frameworks. It then generates optimized runtime engines deployable in the datacenter as well as in automotive and embedded environments.
🔹Simple TensorRT example
🔻Convert the pretrained image segmentation PyTorch model into ONNX.
🔻Import the ONNX model into TensorRT.
🔻Apply optimizations and generate an engine.
🔻Perform inference on the GPU.
⭕️ DO NOT MISS OUT THIS ARTICLE
—————————
📌Via: @cedeeplearning
📌Other social media: https://linktr.ee/cedeeplearning
link: https://devblogs.nvidia.com/speeding-up-deep-learning-inference-using-tensorrt/
#NVIDIA #deeplearning #neuralnetworks #python
#machinelearning #AI