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Master fine-tuning ConvNeXT Vision Transformer for custom dog breed classification using PyTorch and Hugging Face. Learn to process datasets, implement training loops with validation, and deploy your model for accurate predictions.
Learn to classify car brands using transfer learning with Keras and ResNet50. Hands-on tutorial covers dataset preparation, model configuration, training, and prediction visualization.
Learn to build and train a convolutional neural network for chess piece image classification using Python, TensorFlow, and Keras. Covers dataset preparation, model creation, and prediction testing.
Learn to classify natural scenes using TensorFlow and CNN. Build, train, and test a model for image classification with Python, covering dataset preparation, model creation, and prediction.
Learn to classify weather images using transfer learning with Python, TensorFlow, and VGG19. Covers dataset preparation, model implementation, and image prediction.
Learn to build a CNN model using TensorFlow and Keras to predict weather scenes from images. Covers dataset preparation, model creation, training, and testing.
Learn to detect brain tumors using deep learning, CNN, and TensorFlow. Build, train, and test a model for classifying brain images with hands-on coding and practical implementation.
Learn to build a convolutional neural network for flower image classification using TensorFlow and Keras, from dataset preparation to model testing and prediction.
Step-by-step guide to implement and train a Res-UNet model for Melanoma detection using TensorFlow and Keras. Learn to build, train, test, and visualize results for accurate skin lesion segmentation.
Learn to build a YOLOv8-based dog breed detection system using deep learning. Master data preparation, model training, and making predictions with bounding boxes.
Develop a custom YOLOv8 model for real-time basketball object detection, covering automatic labeling, model training, and live inference on game footage.
Learn to create a horse race detection model using deep learning without a pre-existing dataset. Extract frames, automate annotations, train YOLOv8, and apply the model to videos for real-time object detection.
Learn to implement underwater object detection using YOLO-NAS and Python. Covers model import, custom dataset training, and making predictions with bounding boxes for sea images.
Implement object detection for bone fractures using YOLOv8 and Python. Learn to load models, process images, and visualize predictions with hands-on coding examples.
Implement YOLOv8 for ship detection in sea views using Python. Learn data preparation, model training, and prediction visualization for effective object detection.
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