complex relationships. Convolutional Neural Nets (CNNs) were another important breakthrough that enabled learning spatial features in the input. Recurrent Neural Nets (RNNs) facilitated learning from the sequences efficient layers and architectures. Let’s start our journey with learning about embeddings in the next section. Embeddings for Smaller and Faster Models We humans can intuitively grasp similarities between part of modern deep-learning models, and we are excited to explain how they work. In the following section we will explain them through a toy example, but feel free to jump ahead if you are familiar with

are and how to employ them in deep learning workflows. We start with data augmentation in the next section. Data Augmentation Data Augmentation is a set of dataset manipulation techniques to improve sample # Shift towards high tones transform_and_show(image_path, channel_shift_intensity=100) In this section, we discussed a number of spatial and value transformation techniques for image data. We used an the best weights for later use! That’s it for the label invariant image transformations! In this section, we presented various image transformation techniques that can be used to augment an image dataset

ca/~vincentp/ift3395/lectures/backprop_old.pdf GAN:2014 https://papers.nips.cc/paper/5423-generative-adversarial-nets.pdf BigGAN https://arxiv.org/pdf/1809.11096.pdf Ian Goodfellow ▪ How I fail https://veronikach

软件，可以同时获得 Python 解释器、包管理和虚拟环境等一系列 便捷功能，何乐而不为呢。首先从 https://www.anaconda.com/distribution/#download-section 网址进入 Anaconda 下载页面，选择 Python 最新版本的下载链接即可下载，下载完成后安 装即可进入安装程序。如图 1.22 所示，勾选”Add Anaconda to my PATH 参考文献 [1] G. E. Hinton, S. Osindero 和 Y.-W. Teh, “A Fast Learning Algorithm for Deep Belief Nets,” Neural Comput., 卷 18, pp. 1527-1554, 7 2006. [2] Y. LeCun, B. Boser, J. S. Denker, D. Henderson Pouget-Abadie, M. Mirza, B. Xu, D. Warde-Farley, S. Ozair, A. Courville 和 Y. Bengio, “Generative Adversarial Nets,” 出处 Advances in Neural Information Processing Systems 27, Z. Ghahramani, M. Welling, C. Cortes,

J., Mirza, M., Xu, B., Warde‐Farley, D., Ozair, S., ⋯ Bengio, Y. (2014). Generative adversarial nets. Advances in neural information processing systems (pp. 2672–2680). [Gotmare et al., 2018] Gotmare Hochreiter, S., Bengio, Y., Frasconi, P., Schmidhuber, J., & others (2001). Gradient flow in recurrent nets: the difficulty of learning long-term dependencies. [Hochreiter & Schmidhuber, 1997] Hochreiter,

can proceed with installing SAP Data Intelligence. 5 Installing SAP Data Intelligence 3.3 This section describes the installation of SAP Data Intelligence 3.3 on an RKE 2-powered Ku- bernetes cluster from the SAP software center at https://support.sap.com/en/tools/software-logistics-tool- s.html#section_622087154 . Choose "Download SLC Bridge". via the information in the release notes of the SLC Bridge For more details about input parameters for an SAP Data Intelligence 3.3 installation, visit the section Required Input Parameters (https://help.sap.com/viewer/a8d90a56d61a49718e- bcb5f65014bbe7/3.3.l

See 8.22 VBoxManage export on page 280. 1.16 Integrating with Oracle Cloud Infrastructure This section describes how to use the features of Oracle VirtualBox to integrate with Oracle Cloud Infrastructure Apply to save your changes. 1.16.6 Using Oracle VirtualBox With Oracle Cloud Infrastructure This section describes how you can use Oracle VirtualBox with Oracle Cloud Infrastructure to do the following instances launched from the custom image can boot correctly and that network connections will work. This section provides advice on how to prepare a Linux image for export from Oracle VirtualBox. The following

extension packs that are currently installed, please start the VirtualBox Man- ager (see the next section). From the “File” menu, please select “Preferences”. In the window that shows up, go to the “Extensions” snapshot stores the state of the virtual machine and thus occupies some disk space. (See the next section for details on what exactly is stored in a snapshot.) 2. You can restore a snapshot by right-clicking experimental support for Mac OS X Server guests, but this comes with restrictions. Please see the following section as well as chapter 14, Known limitations, page 181. 3.1.1 Mac OS X Server guests Starting with

extension packs that are currently installed, please start the VirtualBox Man- ager (see the next section). From the “File” menu, please select “Preferences”. In the window that shows up, go to the “Extensions” snapshot stores the state of the virtual machine and thus occupies some disk space. (See the next section for details on what exactly is stored in a snapshot.) 2. You can restore a snapshot by right-clicking experimental support for Mac OS X Server guests, but this comes with restrictions. Please see the following section as well as chapter 14, Known limitations, page 178. 3.1.1 Mac OS X Server guests Starting with

extension packs that are currently installed, please start the VirtualBox Man- ager (see the next section). From the “File” menu, please select “Preferences”. In the window that shows up, go to the “Extensions” snapshot stores the state of the virtual machine and thus occupies some disk space. (See the next section for details on what exactly is stored in a snapshot.) 2. You can restore a snapshot by right-clicking experimental support for Mac OS X Server guests, but this comes with restrictions. Please see the following section as well as chapter 14, Known limitations, page 180. 3.1.1 Mac OS X Server guests Starting with