Phil 11.2.18

7:00 – 2:30 ASRC PhD (feeling burned out – went home early for a nap)

  • Continuing with my 810 assignment. Just found out about finite semiotics, which could be useful for trustworthiness detection (variance in terms and speed of adoption)
  • I like this! Creating a Perceptron From Scratch
    • In order to gain more insight as to how Neural Networks (NNs) are created and used, we must first understand how they work. It is important to always create a solid foundation as to why you are doing something, instead of navigating blindly. With the ubiquity of Tensorflow or Keras, sometimes it is easy to forget what you are actually building and how to best develop your NN. For this project I will be using Python to create a simple Perceptron that will implement the basics of Back-Propagation to Optimize our Synapse Weighting. I’ll be sure to explain everything along the way and always encourage you to reach out if you have any questions! I will assume no prior knowledge in NNs, but you will instead need to know some fundamentals of Python programming, low-level calculus, and a bit of linear algebra. If you aren’t quite sure what a NN is and how they are used in the field of AI, I encourage you to first read my article covering that topic before tackling this project. So let’s get to it!
  • And this is very interesting:
    • SHAP (SHapley Additive exPlanations) is a unified approach to explain the output of any machine learning model. SHAP connects game theory with local explanations, uniting several previous methods [1-7] and representing the only possible consistent and locally accurate additive feature attribution method based on expectations (see the SHAP NIPS paper for details).
  • Ok, back to generators. Here are several versions of Call of the Wild
    • Tokens
      index, token
      0, quivering
      1, scraped
      2, introspective
      3, confines
      4, restlessness
      5, pug
      6, mandate
      7, twisted
      8, part
      9, error
      10, thong
      11, resolved
      12, daunted
      13, spray
      14, trees
      15, caught
      16, fearlessly
      17, quite
      18, soft
      19, sounds
      20, slaying
    • Text sequences
      #confg: {"sequence_length":10, "step":1, "type":"words"}
      buck, did, not, read, the, newspapers, or, he, would, have
      did, not, read, the, newspapers, or, he, would, have, known
      not, read, the, newspapers, or, he, would, have, known, that
      read, the, newspapers, or, he, would, have, known, that, trouble
      the, newspapers, or, he, would, have, known, that, trouble, was
      newspapers, or, he, would, have, known, that, trouble, was, brewing
      or, he, would, have, known, that, trouble, was, brewing, not
      he, would, have, known, that, trouble, was, brewing, not, alone
      would, have, known, that, trouble, was, brewing, not, alone, for
      have, known, that, trouble, was, brewing, not, alone, for, himself
      known, that, trouble, was, brewing, not, alone, for, himself, but
      that, trouble, was, brewing, not, alone, for, himself, but, for
      trouble, was, brewing, not, alone, for, himself, but, for, every
      was, brewing, not, alone, for, himself, but, for, every, tidewater
      brewing, not, alone, for, himself, but, for, every, tidewater, dog
      not, alone, for, himself, but, for, every, tidewater, dog, strong
      alone, for, himself, but, for, every, tidewater, dog, strong, of
      for, himself, but, for, every, tidewater, dog, strong, of, muscle
      himself, but, for, every, tidewater, dog, strong, of, muscle, and

       

    • Index sequences
      #confg: {"sequence_length":10, "step":1, "type":"integer"}
      4686, 1720, 283, 1432, 1828, 1112, 4859, 3409, 3396, 379
      1720, 283, 1432, 1828, 1112, 4859, 3409, 3396, 379, 4004
      283, 1432, 1828, 1112, 4859, 3409, 3396, 379, 4004, 3954
      1432, 1828, 1112, 4859, 3409, 3396, 379, 4004, 3954, 4572
      1828, 1112, 4859, 3409, 3396, 379, 4004, 3954, 4572, 4083
      1112, 4859, 3409, 3396, 379, 4004, 3954, 4572, 4083, 3287
      4859, 3409, 3396, 379, 4004, 3954, 4572, 4083, 3287, 283
      3409, 3396, 379, 4004, 3954, 4572, 4083, 3287, 283, 1808
      3396, 379, 4004, 3954, 4572, 4083, 3287, 283, 1808, 975
      379, 4004, 3954, 4572, 4083, 3287, 283, 1808, 975, 532
      4004, 3954, 4572, 4083, 3287, 283, 1808, 975, 532, 973
      3954, 4572, 4083, 3287, 283, 1808, 975, 532, 973, 975
      4572, 4083, 3287, 283, 1808, 975, 532, 973, 975, 4678
      4083, 3287, 283, 1808, 975, 532, 973, 975, 4678, 3017
      3287, 283, 1808, 975, 532, 973, 975, 4678, 3017, 2108
      283, 1808, 975, 532, 973, 975, 4678, 3017, 2108, 984
      1808, 975, 532, 973, 975, 4678, 3017, 2108, 984, 1868
      975, 532, 973, 975, 4678, 3017, 2108, 984, 1868, 3407

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