✿ here is my mini resource guide on AI > ML > DL:
AI ~ θ|1 💮
+ AI resources [list] 🎃
+ AI tools and libraries [list] 🎃
Edge AI & TinyML: [notes] 🦙
Remote Sensing [theory] 🛰️
Deep Learning [theory]
Deep Learning [code]
import gymnasium as gym
import math
import random
import matplotlib
import matplotlib.pyplot as plt
from collections import namedtuple, deque
from itertools import count
import torch
import torch.nn as nn
import torch.optim as optim
import torch.nn.functional as F
env = gym.make("CartPole-v1")
# set up matplotlib
is_ipython = 'inline' in matplotlib.get_backend()
if is_ipython:
from IPython import display
plt.ion()
# if GPU is to be used
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")