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Summary: This guide explores Artificial Intelligence Using Python, from essential libraries like NumPy and Pandas to advanced techniques in machinelearning and deeplearning. Introduction Artificial Intelligence (AI) transforms industries by enabling machines to mimic human intelligence.
Load and Explore Data We load the Telco Customer Churn dataset and perform exploratory data analysis (EDA). EDA is essential for gaining insights into the dataset’s characteristics and identifying any data preprocessing requirements. SupportVectorMachine (svm): Versatile model for linear and non-linear data.
MachineLearning Algorithms Candidates should demonstrate proficiency in a variety of MachineLearning algorithms, including linear regression, logistic regression, decision trees, random forests, supportvectormachines, and neural networks.
Decision Trees: A supervised learning algorithm that creates a tree-like model of decisions and their possible consequences, used for both classification and regression tasks. DeepLearning : A subset of MachineLearning that uses Artificial Neural Networks with multiple hidden layers to learn from complex, high-dimensional data.
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