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Reviewed by Build foundational skills in deep learning by designing and training neural networks to solve complex real-world problems. You'll begin with the essentials of neural networks, advancing to specialized architectures like Convolutional and Recurrent Neural Networks, along with Generative Adversarial Networks. Through projects, create models for applications such as image classification, sentiment analysis, and face generation, gaining hands-on experience s.
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Unlimited Interview Questions
3 Concept Notebooks
3 Practice Quizzes
1 AI-100 Project
1 Real World AI Project
What You’ll Learn:
- Neural network architectures (CNNs, RNNs, Deep Neural Networks)
- NLP fundamentals and transformer models
- Optimization techniques and variance analysis
- Neural style transfer and image processing
What You’ll Build:
- Image detection and recognition system using CNNs
- AI art generator with neural style transfer
- NLP applications: Named Entity Recognition and Question Answering
- Production-ready models in TensorFlow
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Project Content
8 Chapters · 28 lessons · 12 hours of content
Step 1: Install Python
Step 2: Set Up a Virtual Environment
Step 3: Install Required Python Packages
Next Steps