Deep Learning Tuning and Visualization
互动构建和训练网络,管理实验,绘制训练进度,评估准确性,解释预测,调整培训选项以及可视化网络学到的功能
Use Deep Network Designer to interactively build, visualize, edit, and train deep learning network. Tune training options and improve network performance by sweeping hyperparameters or using Bayesian optimization. Use Experiment Manager to manage deep learning experiments that train networks under various initial conditions and compare the results. Monitor training progress using built-in plots of network accuracy and loss. To investigate trained networks, you can use visualization techniques such as Grad-CAM, occlusion sensitivity, LIME, and deep dream. You can also investigate network robustness using adversarial examples and test your trained network by making predictions using new data.
Categories
- Deep Network Designer App
Interactively create and train deep learning networks - 实验经理应用程序
Train networks under multiple initial conditions, interactively tune training options, and assess your results - Deep Learning Tuning
通过编程调整培训选项,从检查站恢复培训并调查对抗性示例 - 深度学习可视化
Plot training progress, assess accuracy, explain predictions, and visualize features learned by a network