Some perspectives I have on Neuroscience, Mathamatics, Machine Learning, and some other areas that I have interests in.
Essentially this is how I found neuroscience and biology to be quite amazing an how they may be such an inspiration to drawn from for designing intelligent algorithms/systems or how "close" they may be to the true "strcuture" in the nature that makes intelligence.
Cognitive Neuroscience PerspectivesBuilding a perspective on the brain.
👀 Sensory, Processing, Affective NeuroscienceFrom sensory to processing to perception.
Searching & Parralel ProcessingReinforcing & searching, some magnificent connection bewteen brain and algorithms.
⚖️ Neural Adaptation With Cost: Systematic Balance DistortionAddiction is a systematic adaptation to deviation, an well rounded circular circuit that feeds into each other. Once balance is distorted, problems may occur.
💭 What We Think Deternmines What We Can ThinkOnce the circuit forms, the rest becomes much easier.
I find theoritical math to be pretty fun. I think that good practical techniques that works well are derived from a theoritical root.
🔢 Unfolding Stochasticity SequentiallyModeling inteactions between stochasticity across time sequentially through the key representational example of Random Walk. Mathamatically & recursively reason sequential stochasticity.
\(N(\mu, \sigma)\) Lend It Some ConfidenceThere are deep connectiosn between statistics and probability, even on very basic statistics level.