《21个项目玩转深度学习———基于TensorFlow的实践详解》配套代码. Contribute to XiaXiaoying/Deep-Learning-21-Examples development by creating an account on GitHub.
Model: CNN, RNN Data type: 1D sequence data Research direction: sequence analysis This example shows how to use deep learning to predict target gene expression with the landmark gene expression data. Model: deep fully connected neural network ...
for example. Deep learning programs have multiple layers of interconnected nodes, with each layer building upon the last to refine and optimize predictions and classifications. Deep learning performs nonlinear transformations to its input and uses what it learns to create ...
Example: ```python model.compile(optimizer=tf.keras.optimizers.Adam(learning_rate=1e-3), loss=tf.keras.losses.BinaryCrossentropy(), metrics=[tf.keras.metrics.BinaryAccuracy(), tf.keras.metrics.FalseNegatives()]) ``` Args: optimizer: String (name of optimizer) or optimizer instance. See `...
This example shows how to use transfer learning to train a deep learning model for multilabel image classification. In binary or multiclass classification, a deep learning model classifies images as belonging to one of two or more classes. The data used to train the network often contains clear...
Deep learning model已经在Computer Vision/ Speech Recognition/ Natural Language Processing几个领域中大放异彩; Deep learning model在Anomaly Detection问题中也已经有明显的效果; Shallow model往往学习不到复杂的特征模式,或者需要对特征进行繁琐(或是先验)的特征工程步骤处理,这种two-phase而不是end-to-end的形式往...
Model building Model training and testing Fish recognition – all together Different learning types Supervised learning Unsupervised learning Semi-supervised learning Reinforcement learning Data size and industry needs Summary Data Modeling in Action - The Titanic Example Linear models for re...
In this study, we developed a deep learning model to identify a user’s mental state based on his/her posting information. To this end, we collected posts from mental health communities in Reddit. By analyzing and learning posting information written by users, our proposed model could ...
Size When you deploy to edge devices such as Raspberry Pi®or FPGAs, choose a model with a low memory footprint, such asSqueezeNetorMobileNet-v2. Products Learn about the products used with deep learning models. Deep Learning Toolbox ...
Deep learning AI models have grown immensely in the last decade, and along with this rapid growth is an explosion in compute resource requirements. Every larger model requires more computational resources and more movement of bits, both in and out of various memory hierarchies and across ...