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NLP
NLP
 
 
OpenCV
OpenCV
 
 
RL
RL
 
 
Transformer
Transformer
 
 
images
images
 
 
.gitignore
.gitignore
 
 
0_Machine_Learning.ipynb
0_Machine_Learning.ipynb
 
 
1-3-Tensor-Concat.ipynb
1-3-Tensor-Concat.ipynb
 
 
1-3-Torch-Classification.ipynb
1-3-Torch-Classification.ipynb
 
 
1-3-Torch-DeepLearning.ipynb
1-3-Torch-DeepLearning.ipynb
 
 
1-3-Torch-Tensor.ipynb
1-3-Torch-Tensor.ipynb
 
 
1-3-WineDataSet-Load.ipynb
1-3-WineDataSet-Load.ipynb
 
 
1-4-DCGAN.ipynb
1-4-DCGAN.ipynb
 
 
1-4-LoRA.ipynb
1-4-LoRA.ipynb
 
 
1-4-Yolo8-tutorial.ipynb
1-4-Yolo8-tutorial.ipynb
 
 
1-5-CNN.ipynb
1-5-CNN.ipynb
 
 
1-5-Torch-MNIST.ipynb
1-5-Torch-MNIST.ipynb
 
 
1-5-cv-lec-05-custom-convnets.ipynb
1-5-cv-lec-05-custom-convnets.ipynb
 
 
1-5-cv-lec-06-data-augmentation.ipynb
1-5-cv-lec-06-data-augmentation.ipynb
 
 
1-5-cv-lec01-convolutional-classifier.ipynb
1-5-cv-lec01-convolutional-classifier.ipynb
 
 
1-5-cv-lec02-convolution-and-relu.ipynb
1-5-cv-lec02-convolution-and-relu.ipynb
 
 
1-5-cv-lec03-maximum-pooling.ipynb
1-5-cv-lec03-maximum-pooling.ipynb
 
 
1-5-cv-lec04-the-sliding-window.ipynb
1-5-cv-lec04-the-sliding-window.ipynb
 
 
2-1-2class-prompt-example.ipynb
2-1-2class-prompt-example.ipynb
 
 
2-1-Deep_Learning_Vector_Similarity.ipynb
2-1-Deep_Learning_Vector_Similarity.ipynb
 
 
2-1-EfficientNet-Weight.ipynb
2-1-EfficientNet-Weight.ipynb
 
 
2-1-EfficientNet.ipynb
2-1-EfficientNet.ipynb
 
 
2-1-IoU.ipynb
2-1-IoU.ipynb
 
 
2-1-Roboflow_EfficientNet_Classification.ipynb
2-1-Roboflow_EfficientNet_Classification.ipynb
 
 
2-1-cnn.ipynb
2-1-cnn.ipynb
 
 
2-2-data_augmentation.ipynb
2-2-data_augmentation.ipynb
 
 
2-2-data_performance.ipynb
2-2-data_performance.ipynb
 
 
2-2-elephant2-yolov5.ipynb
2-2-elephant2-yolov5.ipynb
 
 
2-2-image_feature_vector.ipynb
2-2-image_feature_vector.ipynb
 
 
2-2-object-detection-mp4.ipynb
2-2-object-detection-mp4.ipynb
 
 
2-2-object_detection.ipynb
2-2-object_detection.ipynb
 
 
2-2-object_tracking.ipynb
2-2-object_tracking.ipynb
 
 
2-2-segmentation.ipynb
2-2-segmentation.ipynb
 
 
2-2-train-yolov8-object-detection-on-custom-dataset.ipynb
2-2-train-yolov8-object-detection-on-custom-dataset.ipynb
 
 
2-2-yolo-image-crop.ipynb
2-2-yolo-image-crop.ipynb
 
 
2-2-yolov8-example.ipynb
2-2-yolov8-example.ipynb
 
 
2-3-Detectron2_Tutorial.ipynb
2-3-Detectron2_Tutorial.ipynb
 
 
2-3-YOLOv8.ipynb
2-3-YOLOv8.ipynb
 
 
2-3-classification-performance.ipynb
2-3-classification-performance.ipynb
 
 
2-3-data_augmentation.ipynb
2-3-data_augmentation.ipynb
 
 
2-3-movenet.ipynb
2-3-movenet.ipynb
 
 
2-3-object_counting.ipynb
2-3-object_counting.ipynb
 
 
2-3-object_tracking.ipynb
2-3-object_tracking.ipynb
 
 
2-3-train-yolov8-object-detection-on-custom-dataset.ipynb
2-3-train-yolov8-object-detection-on-custom-dataset.ipynb
 
 
2-4-CIVITAI-text2img.ipynb
2-4-CIVITAI-text2img.ipynb
 
 
2-4-transfer_learning.ipynb
2-4-transfer_learning.ipynb
 
 
2-4-transfer_learning_tutorial.ipynb
2-4-transfer_learning_tutorial.ipynb
 
 
2-5-BLIP.ipynb
2-5-BLIP.ipynb
 
 
2-5-Progressive GAN trained on CelebA for 128x128 images.ipynb
2-5-Progressive GAN trained on CelebA for 128x128 images.ipynb
 
 
2-5-Zero_Shot_Image_Classification.ipynb
2-5-Zero_Shot_Image_Classification.ipynb
 
 
2-5-conditional-image_captioning.ipynb
2-5-conditional-image_captioning.ipynb
 
 
2-5-image-caption.ipynb
2-5-image-caption.ipynb
 
 
2-5-multimodal_q_and_a.ipynb
2-5-multimodal_q_and_a.ipynb
 
 
3-1-segment-tutorial.ipynb
3-1-segment-tutorial.ipynb
 
 
3-10-BUS-Custom_yolov5.ipynb
3-10-BUS-Custom_yolov5.ipynb
 
 
3-3-Yolov8-seg-masks.ipynb
3-3-Yolov8-seg-masks.ipynb
 
 
LICENSE
LICENSE
 
 
README-1-DL.md
README-1-DL.md
 
 
README-2-CNN.md
README-2-CNN.md
 
 
README-NLP.md
README-NLP.md
 
 
README-OpenCV.md
README-OpenCV.md
 
 
README.md
README.md
 
 
Tiger-Woods-keypoint.ipynb
Tiger-Woods-keypoint.ipynb
 
 
counts_coins_20_hough.ipynb
counts_coins_20_hough.ipynb
 
 

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AI-Innovation-2024

AI 핵심 기술 집중 클래스 [교안]

  1. 교육과정명 : AI 핵심 기술 집중 클래스

  2. 교육일정 : 2024년 8월 26일 - 10월 28일(160시간) / 야간 4시간, 18:30-22:30

  3. 교육방식 : 실시간 비대면(ZOOM)

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