introduction to machine learning
Machine learning is a branch of artificial intelligence (AI) that focuses on creating algorithms and statistical models that let computers pick up new skills and enhance existing ones in order to accomplish tasks more effectively. The fundamental principle underlying machine learning is to give computers the ability to learn from data and experience, identify patterns, and make predictions or judgements based on that data. Machine learning comes in three primary flavours: Supervised Learning: In supervised learning, the algorithm is trained on a labelled dataset in which both the input data and the output (labels) are given. To be able to predict outcomes from fresh, unforeseen data, the algorithm must develop a mapping between inputs and outputs. The classification of images, sentiment analysis, and regression issues are examples of common supervised learning tasks. Unsupervised Learning: Unsupervised learning works with unlabeled data, i.e., no predetermined output labels are given