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Reading Notes: The Master Algorithm – Bayesians (part 6)

At heart, Bayes’s theorem is just a simple rule for updating your degree of belief in a hypothesis when you receive new evidence: if the evidence is consistent with the hypothesis, the probability of the hypothesis goes up; if not, it goes down. 1,025 more words


Confessions of a Teenage Boy

I do not claim to vouch for my entire kind. Never, for humanity is too diverse, individuality too intricate, and circumstance too varied for me to do so. 636 more words


Summer Thinking...

At the beginning of the summer, I made a check list of things that I needed to get done, and things I wanted. Honestly, I fell short. 335 more words


The Women Sat

And the women sat

Endearing Thoughts
In relation to present and past
Both with deep insightful journeys of reaching one level unto the next… 48 more words

Reading Notes: The Master Algorithm – Evolutionaries (part 5)

Ronald Fisher’s classic treatise The Genetical Theory of natural Selection formulated the first mathematical theory of evolution.

The key input to a genetic algorithm is a fitness function. 690 more words


Reading Notes: The Master Algorithm – Connectionlists (part 4)

Hebb’s rule is the cornerstone of connectionism. It says knowledge is stored in the connections between neurons.

Donald Hebb stated in his 1949 book The Organization of Behavior: “When an axon of cell A is near enough cell B and repeatedly or persistently takes part in firing it, some growth process or metabolic change takes place in one or both cells such that A’s efficiency, as one the cells firing B, is increased.” It’s often paraphrased as “neurons that fire together wire together.” 424 more words