Artificial intelligence (AI) aims to replicate human thinking in computers. It encompasses various approaches, such as machine learning (ML) and deep learning (DL), which are used to solve AI problems.
to solve a problem by learning from data, instead of explicitly programming the rules.
In DL, neural networks learn to identify important features without the need for traditional feature engineering techniques.
ML is particularly useful in supervised learning, where a model is trained on a dataset containing inputs and known outputs.
The goal is to make predictions for new, unseen data based on the patterns learned from the training set. DL, on the other hand, excels in handling complex datasets like images or text data, where it can automatically extract relevant features.
By leveraging Python programming, developers can harness the power of AI.
Python is a versatile language that offers simplicity, prebuilt libraries, and a supportive community.
It is widely used in AI development due to its ease of learning and platform independence.
Python’s extensive collection of prebuilt libraries, including TensorFlow, Scikit-Learn, and NumP