ML hackathon QUiz

What is the cool new AI created by Cognition that can debug projects and even build apps and websites?

• Cognitify

• CoderX

• Devin

• Builder

What is the full form of GANs?

• Gradient Activation Nodes

• Graphical Association Networks

• Generative Adversarial Networks

• Generalized Algorithm Networks

Which tech mogul had a little tiff with OpenAI? Let's find out!

• Jeff "Alexa, Sue My Rivals" Bezos

• Elon "Mars Needs Coders" Musk

• Bill "Keyboard Warrior" Gates

• Mark "Metaverse Mishap" Zuckerberg

When do we typically unleash the power of KL divergence loss in the realm of machine learning?

• To embark on an epic journey of comparing two probability distributions and unraveling their differences

• To dive into the enchanted realm of measuring the similarity between two sets of images

• To unlock the secrets of comparing the efficiency of different optimization algorithms

• To challenge models for making overly confident predictions and keep them on their toes

Imagine you're embarking on a thrilling machine learning adventure with a limited dataset. Which of these epic splits is most likely ideal for training, validation, and testing your model?

• 90% Train, 5% Validation, 5% Test

• 70% Train, 15% Validation, 15% Test

• 50% Train, 25% Validation, 25% Test

• 30% Train, 35% Validation, 35% Test

What is the term for the exciting stage where we put a machine learning model to the test with unseen data?

• Deployment

• Testing

• Validation

• Training

What does the term "artificial general intelligence" (AGI) really mean?

• A sneaky computer virus

• A cool way to do deep learning

• A super smart machine that can do anything a human can

• A fancy machine learning model just for medical stuff

Which type of learning allows machine learning models to gain knowledge from data without explicit programming?

• Deep learning

• Reinforcement learning

• Unsupervised learning

• Supervised learning

4. What is the name of the loss function represented by this formula?

1/2 * sum((y_true - y_predicted)^2)

(Here, y_true represents the actual values, and y_predicted represents the predicted values by the model.)

Can you guess which loss function is being described here?

• L1 loss

• Hinge loss

• Kullback-Leibler divergence

• Mean Squared Error (MSE)

Which of the following is NOT a key player in the ultimate machine learning dream team?

• Data Preprocessing (cleaning and preparing data)

• Manual Code Writing (writing code for every step of the process)

• Feature Engineering (creating new features from existing data)

• Model Training (fitting the model to the data)