FAI Unit 5 Crossword

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Across
  1. 3. (Cloud-based platform that provides free access to GPUs for AI development.)
  2. 5. (Technology in TensorFlow that automates model building and tuning.)
  3. 7. (Field of AI that deals with understanding and generating human language.)
  4. 8. (Tuning AI models for specific applications.)
  5. 10. (Domain where AI is used for diagnosis and trends.)
  6. 12. (Used for CNNs, RNNs, and transformers.)
  7. 13. (Specialized hardware developed by Google for accelerating AI workloads.)
  8. 15. (Running AI locally without the cloud.)
  9. 18. (PyTorch feature that makes models deployable for production.)
  10. 22. (Amazon Web Services, AI tools with pay-as-you-go.)
  11. 26. (Used to visualize training curves and graphs.)
  12. 27. (A type of AI intelligence inspired by the collective behavior of animals.)
  13. 28. (Google's ML library with Keras integration.)
  14. 29. (Python library often used for handling datasets in AI workflows.)
  15. 30. (Lab under Google that developed Gemini AI.)
  16. 33. (Type of detection in Google Analytics to spot unusual traffic patterns.)
Down
  1. 1. (Type of learning where agents learn through reward and punishment.)
  2. 2. (Dynamic deep learning framework from Meta.)
  3. 4. (AR technique supported by OpenCV to add virtual objects in real scenes.)
  4. 6. (Platform offering cloud-based AI tools.)
  5. 9. (Visualization library built on Matplotlib.)
  6. 11. (Pre-trained and fine-tuned for various tasks.)
  7. 14. (Predicts user behavior and optimizes marketing.)
  8. 16. (Like Siri and Alexa.)
  9. 17. (Google’s service for transcribing speech.)
  10. 19. (Type of neural network architecture behind ChatGPT and Gemini.)
  11. 20. (AI tool for content creation, integrates with Docs/WordPress.)
  12. 21. (A Seaborn plot that shows the distribution and probability density of data.)
  13. 23. (AI that creates content like blogs, ads, etc.)
  14. 24. (Abbreviation for AI that is transparent and explains its decisions.)
  15. 25. (Machine learning task focused on predicting continuous values.)
  16. 31. (Extracting insights from large data sets.)
  17. 32. (High-level API integrated into TensorFlow for building neural networks.)