/Machine-Learning-Notebooks

The full collection of Jupyter Notebook labs from Andrew Ng's new Machine Learning Specialization.

Primary LanguageJupyter NotebookThe UnlicenseUnlicense

Machine Learning Notebooks

#BreakIntoAI with the free-to-audit Machine Learning Specialization. Master fundamental AI concepts and develop practical machine learning skills in the beginner-friendly, 3-course program by AI visionary Andrew Ng.

There are 3 Courses in this Specialization

COURSE 1

Supervised Machine Learning: Regression and Classification

In the first course of the Machine Learning Specialization, you will:

  • Build machine learning models in Python using popular machine learning libraries NumPy and scikit-learn.
  • Build and train supervised machine learning models for prediction and binary classification tasks, including linear regression and logistic regression

COURSE 2

Advanced Learning Algorithms

In the second course of the Machine Learning Specialization, you will:

  • Build and train a neural network with TensorFlow to perform multi-class classification
  • Apply best practices for machine learning development so that your models generalize to data and tasks in the real world
  • Build and use decision trees and tree ensemble methods, including random forests and boosted trees

COURSE 3

Unsupervised Learning, Recommenders, Reinforcement Learning

In the third course of the Machine Learning Specialization, you will:

  • Use unsupervised learning techniques for unsupervised learning: including clustering and anomaly detection.
  • Build recommender systems with a collaborative filtering approach and a content-based deep learning method.
  • Build a deep reinforcement learning model.