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| Tutorial | Description |
| CIFAR10 Caffe Tutorial (UG1335) | Train, quantize, and prune custom CNNs with the CIFAR10 dataset using Caffe and the Xilinx® DNNDK tools. |
| Cats vs Dogs Tutorial (UG1336) | Train, quantize, and prune a modified AlexNet CNN with the Kaggle Cats vs Dogs dataset using Caffe and the Xilinx DNNDK tools. |
| ML SSD PASCAL Caffe Tutorial (UG1340) | Train, quantize, and compile SSD using PASCAL VOC 2007/2012 datasets with the Caffe framework and DNNDK tools, then deploy on a Xilinx ZCU102 target board. |
| DPU Integration Lab (UG1350) | Build a custom system that utilizes the Xilinx Deep Learning Processor (DPU) IP to accelerate machine learning algorithms. |
| Yolov3 Tutorial with Darknet to Caffe Converter and Xilinx DNNDK (UG1334) | Use the Yolov3 example, which converts the Darknet model to Caffe model and uses the DNNDK tool chain for quantization, compilation, and deployment on the FPGA. |
| MNIST Classification with TensorFlow (UG1337) | Learn the DNNDK v3.0 TensorFlow design process for creating a compiled ELF file that is ready for deployment on the Xilinx® DPU accelerator from a simple network model built using Python. This tutorial uses the MNIST test dataset. |
| CIFAR10 Classification with TensorFlow (UG1338) | Learn the DNNDK v3.0 TensorFlow design process for creating a compiled ELF file that is ready for deployment on the Xilinx® DPU accelerator from a simple network model built using Python. This tutorial uses the CIFAR-10 test dataset. |
| Freezing a Keras model for use with DNNDK (UG1380) | Freeze a Keras model by generating a binary protobuf (.pb) file. |
| Deep Learning with custom GoogleNet and ResNet in Keras and Xilinx DNNDK TF 3.0 (UG1381) | Quantize in fixed point some custom CNNs and deploy them on the Xilinx ZCU102 board, using Keras and the Xilinx DNNDK 3.0 tool chain based on TensorFlow (TF). |
| Xilinx AI Model Zoo (UG1389) | Learn how to speed up the deployment of deep learning inference on Xilinx platforms by using free pre-trained deep learning models that cover different applications (such as ADAS/AD, video surveillance, robotics, data center, and so forth). |
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