The best part? You don't need to be a math genius to understand it! Thanks to the user-friendly Scikit-Learn library in Python, Linear Regression becomes a breeze, even for beginners. Introduction: In the exciting world of data science and machine learning, Linear Regression acts as a trusty compass, guiding us toward valuable insights hidden within our data.
isdigit(): sumofcards += int(c) elif c in : sumofcards += 10 else : sumofcards += 11 if sumofcards > 21 : sumofcards -= 11 sumofcards += 1 return sumofcards print ( 'Your Cards: ' ) card1 = draw_card() card2 = draw_card() print (card1, ' and ' ,card2) your_cards = card1 = draw_card() card2 = draw_card() opp_cards = print ( 'Opponent open card: ' ,card2) while cardsum(your_cards) 12 and cardsum(opp_cards) 21 and opp_sum 21 and your_sum your_sum: print ( ' \n Opponent has higher value, Opponent Wins' ) elif opp_sum < your_sum: print ( ' \n You have higher value, You Win' ) else : print ( ' \n Same Value, Tied' ) blackjack() extend() sumofcards = 0 for c in cardlist: if c.
remove(card) return card def cardsum (cardlist): count = cardlist. extend() def draw_card (): card = random. Def blackjack (): import random cardtype = cards = for ct in cardtype: cards.
