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Showing below up to 50 results in range #101 to #150.

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  1. Subplots and gridspec: A more flexible placement (17:05, 17 October 2025)
  2. Overview of the available functions (17:07, 17 October 2025)
  3. Animation and Slider (17:08, 17 October 2025)
  4. Basics (17:12, 17 October 2025)
  5. Sci-kit Overview (17:13, 17 October 2025)
  6. KMeans (17:14, 17 October 2025)
  7. PCA (17:15, 17 October 2025)
  8. FastICA (17:16, 17 October 2025)
  9. Support Vector Machine (17:17, 17 October 2025)
  10. Remove a common signal from your data with SVD (17:18, 17 October 2025)
  11. Scipy.signal: Butterworth low, high and band-pass (17:18, 17 October 2025)
  12. Representation of Numbers in the Computer (10:29, 20 October 2025)
  13. Systematic Programming (10:32, 20 October 2025)
  14. Flow chart symbols (08:31, 21 October 2025)
  15. Examples (08:41, 21 October 2025)
  16. Flow chart for baking bread (08:43, 21 October 2025)
  17. PyWavelets: Wavelet Transforms in Python (09:10, 21 October 2025)
  18. Instantanious Spectral Coherence (09:14, 21 October 2025)
  19. Linearize the spectral coherence (09:16, 21 October 2025)
  20. TQDM: Make your progress visible (09:20, 21 October 2025)
  21. Argh: Organize your command line arguments (09:21, 21 October 2025)
  22. Psutil vs os.cpu count: How many "CPUs" do I have? (09:22, 21 October 2025)
  23. ZeroMQ: Microservices as well as connecting computers via message queue (09:24, 21 October 2025)
  24. Austin: Time and memory profiling (09:27, 21 October 2025)
  25. OpenCV2: Play, write, read a video (09:30, 21 October 2025)
  26. How to read a webcam with CV2 (09:35, 21 October 2025)
  27. Get CUDA ready! (09:46, 21 October 2025)
  28. Converting the original MNIST files into numpy (09:47, 21 October 2025)
  29. Interfacing Data (09:48, 21 October 2025)
  30. Data augmentation (14:23, 21 October 2025)
  31. Layers (14:25, 21 October 2025)
  32. Creating networks (14:28, 21 October 2025)
  33. Train the network (14:32, 21 October 2025)
  34. Write your own layer (14:50, 21 October 2025)
  35. Replace the automatic autograd with your own torch.autograd.Function (14:52, 21 October 2025)
  36. Unfold: How to manually calculate the indices for a sliding 2d window (14:53, 21 October 2025)
  37. How to take advantage of an optimizer for your non-Pytorch project (14:55, 21 October 2025)
  38. How to take advantage of a learning rate scheduler for your non-Pytorch project (14:55, 21 October 2025)
  39. Fisher Exact Test: Test if your performance difference is significant (14:58, 21 October 2025)
  40. Expanding Python with C++ modules (16:04, 21 October 2025)
  41. PyBind11 Stub-Generation (16:05, 21 October 2025)
  42. The fast and furious way (CPU and GPU CUDA) (16:06, 21 October 2025)
  43. Tensorflow / Keras A fast non-introduction (16:11, 21 October 2025)
  44. Symbolic Computation (15:32, 22 October 2025)
  45. 2022: Preparation -- Python class with and without classes (16:05, 22 October 2025)
  46. 2022: Deep Networks and Pytorch (16:08, 22 October 2025)
  47. 2022: Divisive inhibition: a dynamical circuit for change detection (16:11, 22 October 2025)
  48. 2022: Synchronization and dynamic oscillations in the visual system (16:13, 22 October 2025)
  49. 2020: Deep Networks and Tensor Flow (16:14, 22 October 2025)
  50. 2020: Divisive Normalization -- a Universal Concept for Adaptive Dynamics and Function of Cortical Circuits (16:15, 22 October 2025)

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