03/08/2020 - studying

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  • been rather irritable and quarrelsome

  • been feeling rather frustrated after socialising with friends
  • it is not too good for self esteem
  • not their fault, but insecurity rears its ugly head
  • i don't know why i feel a need to justify myself

  • not been sleeping on time
  • probably Liver Fire in TCM terms

  • the machine learning topics are difficult
  • so it is harder to focus
  • i end up experiencing regret at the end of the day
  • so i stay up late trying to make up for lost time
  • not been doing my youtube workouts
  • so kinda frustrated also because i felt like a failure (mildly)
  • i took a morning walk to the mall instead
  • treated myself to mcdonald's and KOI oolong tea
  1. effects of learning from videos and books 
  2. after drinking from the firehose
  3. my info is an unorganised mess
  4. i decided to use the handwriting method
  5.  scribbling handwritten notes on microsoft surface 3 using the windows ink workspace
  6. it is launched from the task bar
  7. and copying those to my evernote notebook
  8. bit by bit i save and bank in those pieces of knowledge
  9. helps clear up my thinking so i feel less frustrated and despondent
  • been toggling between that and andrew ng's course
  • my aim is to understand the math enough to know which methods to use for python library
machine learning - supervised and unsupervised learning
simplest algorithm - linear regression

solving systems of linear equations using matrices
  • linear regression
  • - python.numpy.linalg
  • - solve()
  • - dot()
explanation of cost function and gradient descent
- to find the best fit (line)
- in calculus you can actually do differentiation or find the derivative for the minimum point
- probably gradient descent scales



linear regression cost function and optimisation with gradient descent
- MSE (check for outliers first)
- learning rate
- gradient descent (local minimum == global minimum) for lowest cost

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