https://github.com/jxareas/machine-learning-notebooks

The full collection of Jupyter Notebook labs from Andrew Ng's new Machine Learning Specialization.
https://github.com/jxareas/machine-learning-notebooks

clustering deep-learning jupyter-notebook kmeans learn linear-regression logistic-regression machine-learning machine-learning-algorithms neural-network numpy python regression reinforcement-learning reinforcement-learning-algorithms supervised-learning tensorflow unsupervised-learning

Last synced: 2 days ago
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The full collection of Jupyter Notebook labs from Andrew Ng's new Machine Learning Specialization.

• Host: GitHub
• URL: https://github.com/jxareas/machine-learning-notebooks
• Owner: jxareas
• License: unlicense
• Created: 2022-08-11T05:40:39.000Z (over 2 years ago)
• Default Branch: master
• Last Pushed: 2022-08-12T08:34:22.000Z (over 2 years ago)
• Last Synced: 2025-01-22T19:09:02.140Z (10 days ago)
• Topics: clustering, deep-learning, jupyter-notebook, kmeans, learn, linear-regression, logistic-regression, machine-learning, machine-learning-algorithms, neural-network, numpy, python, regression, reinforcement-learning, reinforcement-learning-algorithms, supervised-learning, tensorflow, unsupervised-learning
• Language: Jupyter Notebook
• Homepage:
• Size: 25.8 MB
• Stars: 257
• Watchers: 6
• Forks: 88
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# Machine Learning Notebooks

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#BreakIntoAI with the free-to-audit [Machine Learning Specialization](https://www.coursera.org/specializations/machine-learning-introduction). 

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.