# NSynth
In a [blog post](https://magenta.tensorflow.org/nsynth-instrument), we describe the details of NSynth (Neural Audio Synthesis), a new approach to audio synthesis using neural networks.
There are three main ways to use NSynth:
* An interactive [AI Experiment](https://g.co/soundmaker) made in collaboration with Google Creative Lab that lets you interpolate between pairs of instruments to create new sounds.
* A MaxForLive Device that integrates into both [Max MSP](https://cycling74.com/products/max/) and [Ableton Live](https://www.ableton.com/en/live/). It allows you to explore the space of NSynth sounds through an intuitive grid interface. [[<b>DOWNLOAD</b>]](http://download.magenta.tensorflow.org/demos/nsynth/NSynthProject.zip)
* Create your own audio samples with the [pretrained network](https://github.com/tensorflow/magenta/tree/master/magenta/models/nsynth).
TensorFlow 1.x Deep Learning Cookbook配套代码
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2018-03-20
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TensorFlow1xDeepLearningCookbook_Code Chapter01 
matrix_manipulations_2.py 754B matrix_manuipulations.py 938B Selecting_devices.py 1KB Tensorflow_ An Introduction 39B add_two_vectors.py 515B tf_upgrade.py 27KB add_two.py 229B validate_tensorflow.py 373B Chapter05 .DS_Store 6KB FULL_labelencoder_trainval.pkl_01.npy 70KB IMDB_1DCNN.ipynb 7KB images 
imagenet_vggnet_table1.png 73KB
space-shuttle4.jpg 82KB parrot_cropped1.jpg 36KB space-shuttle2.jpg 15KB space-shuttle3.jpg 1.93MB imagenet_resnet_identity.png 28KB imagenet_xception_flow.png 62KB parrot.jpg 70KB girl1.jpg 234KB incredible-hulk-180.jpg 82KB cropped_panda.jpg 3KB imagenet_resnet_residual.png 13KB imagenet_inception_module.png 115KB space-shuttle1.jpg 357KB Classifying images with VGGNet, ResNet, Inception, and Xception.ipynb 1.42MB README.md 887B VISUALIZE_TENSORBOARD.ipynb 5KB VGG16_KERAS_VIS_INSPECTION.ipynb 213KB Visual Q&A.ipynb 17KB SENTIMENT_ANALYSIS_TFLEARN.ipynb 4KB nsynth .ipynb_checkpoints Visual Q&A-checkpoint.ipynb 72B 395058__mustardplug__breakbeat-hiphop-a4-4bar-96bpm.wav.npy 5KB Exploring_Neural_Audio_Synthesis_with_NSynth.ipynb 243KB gen_213259__maurolupo__girl-sings-laa.wav 124KB gen_395058__mustardplug__breakbeat-hiphop-a4-4bar-96bpm.wav 156KB model.ckpt-200000.meta 6.73MB 395058__mustardplug__breakbeat-hiphop-a4-4bar-96bpm.wav 1.68MB model.ckpt-200000.index 62KB 213259__maurolupo__girl-sings-laa.wav 2.69MB MNIST_data 
t10k-labels-idx1-ubyte.gz 4KB t10k-images-idx3-ubyte.gz 1.57MB train-images-idx3-ubyte.gz 9.45MB train-labels-idx1-ubyte.gz 28KB FULL_labelencoder_trainval.pkl 231B Chapter04 .ipynb_checkpoints ARTISTIC_STYLE-checkpoint.ipynb 736KB DEEP_DREAM-checkpoint.ipynb 494KB CIFAR_CNN_TLEARN-checkpoint.ipynb 4KB CNN_MINST-checkpoint.ipynb 107KB VGG16_TFLEARN.ipynb 4KB CIFAR_CNN_TLEARN.ipynb 4KB DEEP_DREAM.ipynb 494KB CNN_MINST.ipynb 107KB README.md 17B ARTISTIC_STYLE.ipynb 736KB Chapter03 Readme.md 827B Boston_House_Price_Prediction_MLP.ipynb 184KB Boston_House_Price_Prediction_MLP_with_Keras_Hyperparameter_Tuning.ipynb 229KB Single_Layer_Perceptron.ipynb 4KB Activation_functions.ipynb 84KB Boston_House_Price_Prediction_MLP_with_Keras.ipynb 214KB MNIST_with_BPN_hard_way.py 3KB MNIST_ReLU_cross_entropy.py 2KB Chapter07 Readme.md 330B Restricted_boltzmann_Machines_MNIST.ipynb 57KB PCA_tensorflow.ipynb 110KB K-Means Clustering Iris Dataset.ipynb 64KB Restricted_boltzmann_Machines_Recommender_System.ipynb 38KB Self_Organized_Maps.ipynb 32KB rbm.py 3KB colors.csv 286B Tensorflow_PCA_embeddings.py 1KB Chapter02 Multiple_linear_regression.py 2KB MNIST Softmax.ipynb 18KB Regression 40B Simple_linear_regression.py 2KB Reading_csv_preprocessing.py 2KB MultiLinearRegressor.ipynb 30KB boston_housing.csv 62KB
Software and hardware list.pdf 285KB
README.txt 71B Chapter06 seq2seq-signal-prediction shakespeare.ipynb 13KB shakespeare.py 2KB shakespeare_input.txt 4.36MB char_idx.pickle 926B checkpoint 213B Chapter09 OpenAI_gym.py 769B policy_gradients_pong.py 6KB nn_random_agent.py 3KB Q_learning_cartpole.py 4KB dqn_atari.py 9KB readme.md 211B Chapter08 Readme.md 133B Convolutional_Autoencoder.ipynb 70KB Denoising_Autoencoder.ipynb 1.56MB Stacked_DenoisingAutoencoder_Pretraining.ipynb 78KB Sparse_Autoencoder.ipynb 893KB Autoencoder_image_reconstruction.ipynb 890KB资源评论
