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BeNN

BeNN

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From simple ML algorithms to Neural Networks and Transformers — and from Number Theory to Topology, Cosmology to QED — dive into the world where code meets the cosmos.👨‍💻🌌 For Any Questions @benasphy

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BeNN
BeNN
1 073
I'll be out for long time and wish y'all the best. Looking forward for cool stuff when I come back.

BeNN
BeNN
1 073
Lol😂
Lol😂

BeNN
BeNN
1 073
One way or another the AI bubble gonna hit same graph as dotcom Bubble, but that doesn't mean we won't reach our goal.

BeNN
BeNN
1 073
Repost from Fin Watch
📊 AI Bubble hits same concentration level that resulted in the bursting of previous bubbles, including the Dot Com. @Fin_Wat
📊 AI Bubble hits same concentration level that resulted in the bursting of previous bubbles, including the Dot Com. @Fin_Watch

BeNN
BeNN
1 073

BeNN
BeNN
1 073
Lol There are Levels to this game 😂😂

BeNN
BeNN
1 073
What a Blessed Day! Slot Sacked and We have UCL Final🔥

BeNN
BeNN
1 073
Tg is also gonna stop P2P in Ethiopia! what other options is left guys👀

BeNN
BeNN
1 073
Lol😂😂TokenMaxxing at its peak
Lol😂😂TokenMaxxing at its peak

BeNN
BeNN
1 073
Remember It's Better to fail at something you Love than to Succeed at something you don't Love!

BeNN
BeNN
1 073
Unpopular Opinion: Use X instead of YouTube for Tutorial!

BeNN
BeNN
1 073
Eid al-Adha Mubarak to everyone 🌙
Eid al-Adha Mubarak to everyone 🌙

BeNN
BeNN
1 073
Final Output

BeNN
BeNN
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The Second project is Cliff Walking and I used Proximal Policy Optimization(PPO) Gymnasium: https://gymnasium.farama.org/environments/toy_text/cliff_walking/ Github: https://github.com/benasphy/OpenAI-s_Gym_library_Project/tree/main/Cliff_Walking

BeNN
BeNN
1 073
Fun Fact: Incase you have watched Viking Series or Heard about it, Ivar The Boneless and Bjorn IronSide has the same Mother in Real History unlike the series. @BeNN_Pi

BeNN
BeNN
1 073
What a sad day for Live and city fans😔What an Era it was. CityPool was sth else! Hope it continues that way.

BeNN
BeNN
1 073
The Final Output

BeNN
BeNN
1 073
8x8 after tweaking the epsilon greedy parameters and others
8x8 after tweaking the epsilon greedy parameters and others

BeNN
BeNN
1 073
8x8 grid and obviously more noise
8x8 grid and obviously more noise

BeNN
BeNN
1 073
4x4 Grid output, as you can see there is a less noise and the model is effectively using Q-Learning Table to find optimal pat
4x4 Grid output, as you can see there is a less noise and the model is effectively using Q-Learning Table to find optimal path after like 2000 episodes.