https://github.com/ndrplz/machine_learning_lectures

Collection of lectures and lab lectures on machine learning and deep learning. Lab practices in Python and TensorFlow.
https://github.com/ndrplz/machine_learning_lectures

deep-learning deep-learning-tutorial deep-neural-networks lecture-material lecture-notes machine-learning machine-learning-algorithms machine-learning-tutorials reinforcement-learning tensorflow tensorflow-tutorials tutorial-exercises tutorials

Last synced: 3 months ago
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Collection of lectures and lab lectures on machine learning and deep learning. Lab practices in Python and TensorFlow.

• Host: GitHub
• URL: https://github.com/ndrplz/machine_learning_lectures
• Owner: ndrplz
• Created: 2016-12-11T16:38:07.000Z (about 8 years ago)
• Default Branch: master
• Last Pushed: 2019-12-03T02:02:44.000Z (about 5 years ago)
• Last Synced: 2024-09-27T21:02:30.326Z (4 months ago)
• Topics: deep-learning, deep-learning-tutorial, deep-neural-networks, lecture-material, lecture-notes, machine-learning, machine-learning-algorithms, machine-learning-tutorials, reinforcement-learning, tensorflow, tensorflow-tutorials, tutorial-exercises, tutorials
• Language: TeX
• Homepage: https://ndrplz.github.io/machine_learning_lectures/
• Size: 81.2 MB
• Stars: 145
• Watchers: 14
• Forks: 45
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# machine_learning_lectures

**Collection of lectures and lab lectures on machine learning and deep learning.**

---

## Deep Learning

### Gradient Descent






LaTeX source: [here](https://github.com/ndrplz/machine_learning_lectures/tree/master/slides/deep_learning/gradient_descent).




Practice (1) [slides](https://github.com/ndrplz/machine_learning_lectures/blob/master/lab/tensorflow_introduction/tex/tensorflow_intro.pdf).




Practice (2) [slides](https://github.com/ndrplz/machine_learning_lectures/blob/master/lab/tensorflow_linear_regression/tex/tensorflow_regression.pdf) and [code](https://github.com/ndrplz/machine_learning_lectures/tree/master/lab/tensorflow_linear_regression/code) (TensorFlow).

### Neural Networks and Deep Neural Networks






LaTeX source: [here](https://github.com/ndrplz/machine_learning_lectures/blob/master/slides/deep_learning/deep_neural_networks/).




Practice [slides](https://github.com/ndrplz/machine_learning_lectures/blob/master/lab/tensorflow_neural_network/tex/tensorflow_neural_nets.pdf) and [code](https://github.com/ndrplz/machine_learning_lectures/tree/master/lab/tensorflow_neural_network/code) (TensorFlow).

### Convolutional Neural Networks






LaTeX source: [here](https://github.com/ndrplz/machine_learning_lectures/tree/master/slides/deep_learning/convolutional_neural_networks).




Practice [slides](https://github.com/ndrplz/machine_learning_lectures/blob/master/lab/tensorflow_convolutional_nets/tex/tensorflow_convnets.pdf) and [code](https://github.com/ndrplz/machine_learning_lectures/tree/master/lab/tensorflow_convolutional_nets/code) (TensorFlow).

### Recurrent Neural Networks






LaTeX source: [here](https://github.com/ndrplz/machine_learning_lectures/tree/master/slides/deep_learning/recurrent_neural_networks).




Practice [slides](https://github.com/ndrplz/machine_learning_lectures/blob/master/lab/tensorflow_recurrent_nets/tex/tensorflow_lstm.pdf) and [code](https://github.com/ndrplz/machine_learning_lectures/tree/master/lab/tensorflow_recurrent_nets/code) (TensorFlow).

---

## Reinforcement Learning

### Introduction and Model Free Learning






LaTeX source: [here](https://github.com/ndrplz/machine_learning_lectures/blob/master/slides/reinforcement_learning/01_introduction_and_model_free_learning/).




Practice [slides](https://github.com/ndrplz/machine_learning_lectures/blob/master/lab/q_learning/tex/q_learning.pdf) and [code](https://github.com/ndrplz/machine_learning_lectures/tree/master/lab/q_learning/code) (TensorFlow).

### Function Approximation






LaTeX source: [here](https://github.com/ndrplz/machine_learning_lectures/blob/master/slides/reinforcement_learning/02_function_approximation/).

---

## Machine Learning

### Boosting






LaTeX source: [here](https://github.com/ndrplz/machine_learning_lectures/tree/master/lab/boosting/tex).




Practice code: [here](https://github.com/ndrplz/machine_learning_lectures/tree/master/lab/boosting/code).

### Clustering






LaTeX source: [here](https://github.com/ndrplz/machine_learning_lectures/tree/master/lab/clustering/tex).




Practice code: [here](https://github.com/ndrplz/machine_learning_lectures/tree/master/lab/clustering/code).

### Dimensionality Reduction






LaTeX source: [here](https://github.com/ndrplz/machine_learning_lectures/tree/master/lab/dimensionality_reduction/tex).




Practice code: [here](https://github.com/ndrplz/machine_learning_lectures/tree/master/lab/dimensionality_reduction/code).

### Logistic Regression






LaTeX source: [here](https://github.com/ndrplz/machine_learning_lectures/tree/master/lab/logistic_regression/tex).




Practice code: [here](https://github.com/ndrplz/machine_learning_lectures/tree/master/lab/logistic_regression/code).

### Naive Bayes






LaTeX source: [here](https://github.com/ndrplz/machine_learning_lectures/tree/master/lab/naive_bayes/tex).




Practice code: [here](https://github.com/ndrplz/machine_learning_lectures/tree/master/lab/naive_bayes/code).

### Support Vector Machine (SVM)






LaTeX source: [here](https://github.com/ndrplz/machine_learning_lectures/tree/master/lab/support_vector_machines/tex).




Practice code: [here](https://github.com/ndrplz/machine_learning_lectures/tree/master/lab/support_vector_machines/code).

## F.A.Q.

* **How did you make the thumbnails?** 

Please see [`make_thumbs.py`](./make_thumbs.py). The script assumes that [ImageMagick](https://imagemagick.org/index.php) library is already installed in your system.