Learn Machine Learning
A comprehensive learning path to master machine learning, from mathematical foundations to deep learning and real-world model deployment.
7 matières à étudier
Mathematics for ML
Build a strong foundation in linear algebra, calculus, probability, and statistics essential for machine learning.
Commencer à apprendrePython for Data Science
Learn Python programming with NumPy, Pandas, and Matplotlib for data manipulation and visualization.
Commencer à apprendreSupervised Learning
Understand regression, classification, decision trees, SVMs, and ensemble methods like Random Forests and XGBoost.
Commencer à apprendreUnsupervised Learning
Explore clustering, dimensionality reduction, anomaly detection, and generative models.
Commencer à apprendreDeep Learning Fundamentals
Learn neural networks, backpropagation, CNNs, RNNs, and training techniques using PyTorch or TensorFlow.
Commencer à apprendreNatural Language Processing
Study text processing, word embeddings, transformers, and large language models.
Commencer à apprendreMLOps & Model Deployment
Deploy models to production with MLflow, Docker, model serving, monitoring, and A/B testing.
Commencer à apprendreParcours connexes
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