Posts

Diving Deep into a Research Paper

NetworkX as a graphing tool in python

Page Rank Algorithm

for those beginning Deep Learning

BERT: Bi-directional transformer for language understanding

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SAGAN: Self-Attention Generative Adversarial Networks

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CENTER

 NEW one ain't rich aint a bitch is kinder  acts like a reminder a reminder of hope ain't a victim

Self-Supervised learning for dumber kids......

Reinforcement Learning for Dumb Kids-(agent, environment, reward, punishment, action)

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  Hola, todays article will cover the basics of Reinforcement learning, we will focus on RL basics cause the advanced concepts are tough, and i myself cant explain them. so RL in nibba terms, is just real life, we try to survive in our surrounding, surroundings are either know to us, or unknow to us, but due the the hardwired instincts we have, we can survive, and not only surviving ,  we have been dominating planet earth for last 10,000 years. Now what is reinforcement learning, let me introduce some terms for that  *agents *reward *punishment *environment "agent seeks reward in the environment and avoids punishment."      so u get idea right, its based on reward and punishment, but how is it different than machine learning well we aint working on data, we are interacting with the environment. some basic facts: RL is based on environments, so many parameters come into play, basically they variables are infinite. scenarios are real world. broader in sense. objective is to rea