Get Answers to Your Most Common ML Questions
Machine Learning is a subset of AI that enables computers to learn from data and improve over time without being explicitly programmed.
Supervised, Unsupervised, Semi-supervised, and Reinforcement Learning.
In supervised learning, models are trained using labeled data, where the input and expected output are known.
Overfitting occurs when the model learns noise and details in training data, reducing its performance on unseen data.
A table used to evaluate the performance of a classification model by comparing predicted and actual results.
It is the process of selecting, modifying, or creating new input features to improve model performance.
Scikit-learn, TensorFlow, PyTorch, XGBoost, LightGBM, and Keras.
An optimization algorithm used to minimize the loss function in machine learning models.
A method to assess how a model will perform on unseen data by dividing the dataset into training and validation sets multiple times.
A computational model inspired by the human brain, used especially in deep learning for recognizing patterns.