Keras
Keras is an open source, cross platform, and user friendly neural network library written in Python. It is capable of running on top of TensorFlow, Microsoft Cognitive Toolkit, R, Theano, and PlaidML.
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Visualizer for neural network, deep learning and machine learning models
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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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Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow
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Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
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100-Days-Of-ML-Code中文版
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ncnn is a high-performance neural network inference framework optimized for the mobile platform
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🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.
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Open standard for machine learning interoperability
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A neural network that transforms a design mock-up into a static website.
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Essential Cheat Sheets for deep learning and machine learning researchers https://medium.com/@kailashahirwar/essential-cheat-sheets-for-machine-learning-and-deep-learning-researchers-efb6a8ebd2e5
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Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.
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The AI developer platform. Use Weights & Biases to train and fine-tune models, and manage models from experimentation to production.
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Keras implementations of Generative Adversarial Networks.
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AutoML library for deep learning
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Techniques for deep learning with satellite & aerial imagery
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Flexible and powerful tensor operations for readable and reliable code (for pytorch, jax, TF and others)
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A Deep-Learning-Based Chinese Speech Recognition System 基于深度学习的中文语音识别系统
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Created by François Chollet
Released March 27, 2015
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- 441 followers
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- keras-team
- Website
- keras.io
- Wikipedia
- Wikipedia