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: 9 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 9 years ago)
- Default Branch: master
- Last Pushed: 2019-12-03T02:02:44.000Z (about 6 years ago)
- Last Synced: 2025-04-07T01:53:09.534Z (10 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: 149
- Watchers: 13
- Forks: 44
- 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.