Introduction to Machine Learning

Python Fundamentals for Machine Learning

Data Preprocessing and Exploration

Supervised Learning Algorithms

Unsupervised Learning Algorithms

Evaluation and Validation of Machine Learning Models

Feature Selection and Engineering

Ensemble Learning

Neural Networks and Deep Learning

Model Tuning and Hyperparameter Optimization

Introduction to Natural Language Processing (NLP)

Introduction to Recommender Systems

Model Deployment and Deployment

Ethical Considerations and Bias in Machine Learning

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