Explore practical AI projects, including chatbots, sentiment analysis, image classification, advanced face recognition
Sub Category
- Data Science
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Objectives
- Building chatbots using Keras. Sentiment analysis implementation with recurrent neural networks (RNN).
- Image classification techniques using Keras. Advanced face recognition applications using computer vision and deep learning.
- Practical project implementation on Google Colab. Text preprocessing techniques like Bow Model, Count Vectorizer, Stemming, and Lemmatization.
- Model training, evaluation, and prediction. Pretrained model utilization and fine-tuning. Image preprocessing, augmentation, and visualization.
- Face detection and recognition algorithms. Embedding generation and classification. Real-world implementation and testing of AI models.
Pre Requisites
- Python programming language.
- Fundamentals of machine learning and deep learning concepts.
FAQ
- Q. How long do I have access to the course materials?
- A. You can view and review the lecture materials indefinitely, like an on-demand channel.
- Q. Can I take my courses with me wherever I go?
- A. Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don't have an internet connection, some instructors also let their students download course lectures. That's up to the instructor though, so make sure you get on their good side!
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