Test Your AI Skills With Our AI Quiz!

AI shares close ties with Computer Science, encompassing the formulation of algorithms and structures enabling machines to perform tasks typically requiring human cognitive abilities

AI stands for Artificial Intelligence, which refers to the simulation of human intelligence processes by machines, especially computer systems

The primary goal of AI is to achieve autonomous intelligence, where machines can perform tasks and make decisions without human intervention

Python is a popular programming language used in AI development due to its simplicity and a wide range of libraries for machine learning and data analysis

The Turing Test evaluates a machine's capability to exhibit intelligent behavior indistinguishable from a human, conceived by Alan Turing in 1950

Supervised learning involves training a model using labeled data. In this method, the model learns to establish a connection between input features and output labels based on provided examples.

The loss function in machine learning quantifies the disparity between model predictions and actual target values. Minimizing this disparity during training aids in refining the model's predictions.

The ReLU (Rectified Linear Activation) is commonly employed in hidden layers of neural networks due to its effectiveness in training and its ability to counter the vanishing gradient problem.

RNN (Recurrent Neural Network) is particularly suitable for sequential data processing. Its capability to maintain a memory of past inputs makes it valuable for tasks like time series analysis and natural language processing.

NumPy is a fundamental Python library catering to numerical computations. Its support for arrays, matrices, and mathematical functions makes it an essential tool for scientific computing and machine learning.

Neural networks are a computational model inspired by the structure and function of the human brain, consisting of interconnected nodes (artificial neurons) that process and transmit information

Machine learning, a subset of AI, involves creating algorithms enabling computers to learn from data and make predictions or decisions autonomously

Reinforcement learning is an AI technique where an agent learns to perform actions in an environment to maximize cumulative rewards by receiving feedback in the form of rewards or penalties

Image Compression is not categorized as a machine learning algorithm; it functions as a technique aimed at reducing image file sizes while maintaining visual quality.

pandas is a widely used Python library for data manipulation and analysis. It provides various data structures and functions that facilitate tasks such as data cleaning, exploration, and transformation.

The activation function within a neuron serves the purpose of introducing non-linearity to the output. This allows neural networks to learn intricate relationships within data, crucial for solving complex problems.

The bias term in a neural network neuron is responsible for introducing a shift in the activation function. By doing so, it assists in learning, even when input values are all zero.

The Global Interpreter Lock (GIL) is a mutex in Python that permits only one thread to execute Python bytecode at a time within a single process. This constraint, while simplifying memory management, can limit performance gains from multithreading, primarily in the CPython interpreter

Support Vector Machine (SVM) is a supervised learning algorithm applicable to both classification and regression tasks, depending on the specific type of SVM utilized.