Machine Learning
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10 lessons3 levels1 capstone project
Learn supervised and unsupervised learning, regression, classification, trees, ensembles, clustering, recommendation basics and the end-to-end model-development workflow.
BASIC
- Machine Learning with Python and Scikit-Learn — freeCodeCamp (Full course)
to regression, classification, trees, boosting, clustering and deployment. - Machine Learning Full Course for Beginners (Long)
Broad overview of the ML workflow, algorithms and feature engineering. - Beginner to Advanced — Complete ML Tutorial (Long)
Practical scikit-learn implementation across common modeling patterns.
INTERMEDIATE
- Practical Deep Learning Lesson 1 — fast.ai
Apply Machine Learning through the adjacent capability: Data Science Foundations. - Introduction to Random Forests — fast.ai
Apply Machine Learning through the adjacent capability: Data Science Foundations. - The Basics of Evaluating Machine Learning Projects
Apply Machine Learning through the adjacent capability: Feature Engineering & Model Evaluation.
ADVANCED
- Step by Step — Simple Neural Network with TensorFlow
Extend Machine Learning into senior/production practice through Deep Learning. - OpenCV Course with Python — freeCodeCamp
Extend Machine Learning into senior/production practice through Computer Vision. - End-to-End NLP Project in Python
Extend Machine Learning into senior/production practice through Natural Language Processing (NLP).