Tensors and Dynamic neural networks in Python with strong GPU acceleration
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Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.
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NumPy & SciPy for GPU
tensorboard for pytorch (and chainer, mxnet, numpy, ...)
Read and write Neuroglancer datasets programmatically.