DSP, Natural language - Computer Science 7
Advanced
Technical
Computer Science
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Signals and systems (digital signal processing)25Lessons ·
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1. Signals and Systems
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2. Discrete-Time (DT) Systems
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3. Feedback, Poles, and Fundamental Modes
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4. Continuous-Time (CT) Systems
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5. Z Transform
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6. Laplace Transform
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7. Discrete Approximation of Continuous-Time Systems
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8. Convolution
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9. Frequency Response
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10. Feedback and Control
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11. Continuous-Time (CT) Frequency Response and Bode Plot
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12. Continuous-Time (CT) Feedback and Control, Part 1
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13. Continuous-Time (CT) Feedback and Control, Part 2
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14. Fourier Representations
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15. Fourier Series
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16. Fourier Transform
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17. Discrete-Time (DT) Frequency Representations
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18. Discrete-Time (DT) Fourier Representations
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19. Relations Among Fourier Representations
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20. Applications of Fourier Transforms
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21. Sampling
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22. Sampling and Quantization
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23. Modulation, Part 1
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24. Modulation, Part 2
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25. Audio CD
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Natural language understanding15Lessons ·
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Lecture 1 – Course Overview | Stanford CS224U: Natural Language Understanding | Spring 2019
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Lecture 2 – Word Vectors 1 | Stanford CS224U: Natural Language Understanding | Spring 2019
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Lecture 3 – Word Vectors 2 | Stanford CS224U: Natural Language Understanding | Spring 2019
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Lecture 4 – Word Vectors 3 | Stanford CS224U: Natural Language Understanding | Spring 2019
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Lecture 5 – Sentiment Analysis 1 | Stanford CS224U: Natural Language Understanding | Spring 2019
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Lecture 6 – Sentiment Analysis 2 | Stanford CS224U: Natural Language Understanding | Spring 2019
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Lecture 7 – Relation Extraction | Stanford CS224U: Natural Language Understanding | Spring 2019
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Lecture 8 – NLI 1 | Stanford CS224U: Natural Language Understanding | Spring 2019
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Lecture 9 – NLI 2 | Stanford CS224U: Natural Language Understanding | Spring 2019
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Lecture 10 – Grounding | Stanford CS224U: Natural Language Understanding | Spring 2019
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Lecture 11 – Semantic Parsing | Stanford CS224U: Natural Language Understanding | Spring 2019
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Lecture 12 – Evaluation Methods | Stanford CS224U: Natural Language Understanding | Spring 2019
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Lecture 13 – Evaluation Metrics | Stanford CS224U: Natural Language Understanding | Spring 2019
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Lecture 14 – Contextual Vectors | Stanford CS224U: Natural Language Understanding | Spring 2019
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Lecture 15 – Presenting Your Work | Stanford CS224U: Natural Language Understanding | Spring 2019
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Intelligent mobile applications3Lessons ·
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TensorFlow Lite for iOS (Coding TensorFlow)
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Swift for TensorFlow: The Next-Generation Machine Learning Framework (TF Dev Summit '19)
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TensorFlow Lite for Android (Coding TensorFlow)
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Computer vision2Lessons ·
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MIT 6.S094: Computer Vision
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OpenCV Course - Full Tutorial with Python
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Robotics23Lessons ·
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Lecture 1 | MIT 6.832 Underactuated Robotics, Spring 2009
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Lecture 2 | MIT 6.832 Underactuated Robotics, Spring 2009
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Lecture 3 | MIT 6.832 Underactuated Robotics, Spring 2009
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Lecture 4 | MIT 6.832 Underactuated Robotics, Spring 2009
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Lecture 5 | MIT 6.832 Underactuated Robotics, Spring 2009
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Lecture 6 | MIT 6.832 Underactuated Robotics, Spring 2009
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Lecture 7 | MIT 6.832 Underactuated Robotics, Spring 2009
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Lecture 8 | MIT 6.832 Underactuated Robotics, Spring 2009
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Lecture 9 | MIT 6.832 Underactuated Robotics, Spring 2009
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Lecture 10 | MIT 6.832 Underactuated Robotics, Spring 2009
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Lecture 11 | MIT 6.832 Underactuated Robotics, Spring 2009
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Lecture 12 | MIT 6.832 Underactuated Robotics, Spring 2009
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Lecture 13 | MIT 6.832 Underactuated Robotics, Spring 2009
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Lecture 14 | MIT 6.832 Underactuated Robotics, Spring 2009
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Lecture 15 | MIT 6.832 Underactuated Robotics, Spring 2009
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Lecture 16 | MIT 6.832 Underactuated Robotics, Spring 2009
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Lecture 17 | MIT 6.832 Underactuated Robotics, Spring 2009
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Lecture 18 | MIT 6.832 Underactuated Robotics, Spring 2009
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Lecture 19 | MIT 6.832 Underactuated Robotics, Spring 2009
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Lecture 20 | MIT 6.832 Underactuated Robotics, Spring 2009
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Lecture 21 | MIT 6.832 Underactuated Robotics, Spring 2009
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Lecture 22 | MIT 6.832 Underactuated Robotics, Spring 2009
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Lecture 23 | MIT 6.832 Underactuated Robotics, Spring 2009
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