NumPy & Neural Network Experiments in Python | Full Practical Guide DAY 4
Автор: Skill-Plus
Загружено: 2025-08-30
Просмотров: 7
Описание:
In this video, we dive into a series of exciting deep learning and NLP topics. First, we explore transfer learning with MobileNet and VGG16, where we fine-tune a pre-trained model on a small image dataset for efficient image classification. Next, we shift to real-time image classification using OpenCV and a pre-trained CNN model to process webcam input and display predictions live.
We also introduce the Transformer architecture, showing how to tokenize and encode text using HuggingFace’s transformers, and analyze the behavior of transformer layers. In the NLP domain, we fine-tune BERT for sentiment analysis, using a confusion matrix and accuracy metrics to evaluate its performance.
We also showcase GPT-2 for text generation, experimenting with parameters like temperature and max tokens for optimal text outputs. Lastly, we use T5 for text summarization, comparing the quality of automatic summaries using metrics like ROUGE.
This video is packed with practical implementations and real-world applications, from image processing to advanced NLP techniques.
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