Machine Learning and AI with Python
The concepts, neural-network architectures, libraries and MLOps tools that make Python the language of artificial intelligence.
Intermediate
Start with the concepts (supervised vs unsupervised learning, evaluation), build classic models with scikit-learn, then move to deep learning with PyTorch or TensorFlow.
Sub-topics (4)
Machine Learning Concepts
Learning paradigms, tasks and the workflow of building a model.
Intermediate♥ 0🔖 0💬 0
Neural Network Architectures
Perceptrons, MLPs, CNNs, RNNs, Transformers, GNNs and generative models.
Advanced♥ 0🔖 0💬 0
Machine Learning Libraries
scikit-learn, gradient boosting, deep-learning frameworks and model formats.
Intermediate♥ 0🔖 0💬 0
MLOps and Experiment Tracking
Track experiments, version models and monitor them in production.
Advanced♥ 0🔖 0💬 0
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