Interview Questions

Bless M. - "You can ask some clarifying questions like 1) Ask if the list is already sorted or not 2) is zero included in the list ? 3) Natural numbers are usually positive numbers ( clarify they are non negatives) Solution : 1) If sorted use two pointers and sort them in O(N) 2) if not sorted , -ve / only +ve numbers in the list doesn't matter - the easiest solution is Use a priority queue and push the number and its square in each iteration Finally return the list returned by the priority Queue. N"See full answer

Yash N. - "import time class Task: def init\(self, description, interval=None): self.description = description self.interval = interval self.next_run = time.time() class SimpleTaskScheduler: def init\(self): self.tasks = [] def add_task(self, description, interval=None): self.tasks.append(Task(description, interval)) def run(self, duration=60): end_time = time.time() + duration while time.time() < end_time: curr"See full answer

Isnadea soraya R. - "untuk mengurutkan daftar angka secara efisien saya akan menggunakan aplikasi pengolah angka yaitu excel dengan rumus rumus untuk mempermudah dan mempercepat pengurutan daftar angka"See full answer

Praveen D. - "Grandma! You know how we can look at a picture and know what's in it—like seeing a cat or a dog? Computers can learn to do that too! It's just they use special tricks and math to see and understand pictures or videos. It helps them figure out what's in the pictures, almost like how we do! Almost like giving it eyes to see the world in its own way!"See full answer

Anonymous Aardvark - "in simple words, linear regression helps in predicting the value whereas logistics regression helps in predicting the binary classification. But lets talk through some example Linear regression model: E-commerce website pricing recommendation engine is built on linear regression model where we do have some variables such as competitor price, internal economics and consumer demand etc when we put this in a supervised learning model, it helps in predicting prices Logistics regression model"See full answer

Vijay S. - "Which one I critical, is the erratic change in the delivery cycle is one you need to investigate and further deep dive into to find the root cause"See full answer

Anonymous Hare - "Sharing the approach for functional requirements we tool to solve this question. Functional Requirements This is only for the Registered users What is a "For You" page ? Home page where you get suggestions based on people you follow. Interactions like/share/comments (done by user) Interests (shared by the user during registration or onboarding) sports choices/ region choices/ Video sharing platform. So how many videos should we s"See full answer

Dinar M. - "Even more faster and vectorized version, using np.linalg.norm - to avoid loop and np.argpartition to select lowest k. We dont need to sort whole array - we need to be sure that first k elements are lower than the rest. import numpy as np def knn(Xtrain, ytrain, X_new, k): distances = np.linalg.norm(Xtrain - Xnew, axis=1) k_indices = np.argpartition(distances, k)[:k] # O(N) selection instead of O(N log N) sort return int(np.sum(ytrain[kindices]) > k / 2.0) `"See full answer

Bhavya V. - "Overfitting is the condition where your model is giving an unexpectedly higher accuracy because of its training in a small database and not getting exposed to anu different type of database while testing"See full answer