AI's gaming algorithm: minimax 🎮 anticipates opponent moves by assuming they aim to minimize it's gains.For each game choice, it plays out every possible game outcome evaluating which move optimizes victory chance, predicting & countering opponents' actions throughout the game🤖

Lets calculate time complexity 📊 for num in arr: # (n 1) if num % 2 == 0: #(n if executed) print("Even") else: #(n if executed) print("Odd") complexity: O(n) 🚀 #Algorithms #DSA

🧠 Neural networks, in a nutshell, mimic the human brain. A neural network contains layer(s), every layer contains one or more artificial neurons which take input, perform computations, and deliver an output. The layers come together to perform complex tasks. #AI #DeepLearning

Lets calculate time complexity 📊 time taken by : for loop ➡️ n 1 a statement inside loop ➡️n Code: for i in range(len(arr)): # (n 1) for j in range(len(arr)): # n(n 1) print(arr[i] arr[j]) # n*n = n² Time complexity: O(n²) 🚀 #Algorithms #DSA

Important factors to analyze an algorithm's efficiency: ⏱️ Time Complexity: Measures execution time efficiency 💾💿 Space Complexity: Evaluates variable usage 🛜 Network/Data Transfer ⚡ Power Consumption 🖥️ CPU Register Consumption #AlgorithmAnalysis #TechKnowledge 🚀