A collection of machine learning examples and tutorials.
Find associated tutorials at https://lazyprogrammer.me
Find associated courses at https://deeplearningcourses.com
Please note that not all code from all courses will be found in this repository. Some newer code examples (e.g. most of Tensorflow 2.0) were done in Google Colab. Therefore, you should check the instructions given in the lectures for the course you are taking.
The code for each course is separated by folder. You can determine which folder corresponds with which course by watching the "Where to get the code" lecture inside the course (usually Lecture 2 or 3).
Remember: one folder = one course.
I've noticed that many people have out-of-date forks. Thus, I recommend not forking this repository if you take one of my courses. I am constantly updating my courses, and your fork will soon become out-of-date. You should clone the repository instead to make it easy to get updates (i.e. just "git pull" randomly and frequently).
Beginning with Tensorflow 2, I started to use Google Colab. For those courses, unless otherwise noted, the code will be on Google Colab. Links to the notebooks are provided in the course. See the lecture "Where to get the code" for further details.
Data Science: Transformers for Natural Language Processing
https://deeplearningcourses.com/c/data-science-transformers-nlp
Machine Learning: Natural Language Processing in Python (V2)
https://deeplearningcourses.com/c/natural-language-processing-in-python
Time Series Analysis, Forecasting, and Machine Learning
https://deeplearningcourses.com/c/time-series-analysis
Financial Engineering and Artificial Intelligence in Python
https://deeplearningcourses.com/c/ai-finance
PyTorch: Deep Learning and Artificial Intelligence
https://deeplearningcourses.com/c/pytorch-deep-learning
Tensorflow 2.0: Deep Learning and Artificial Intelligence (VIP Version)
https://deeplearningcourses.com/c/deep-learning-tensorflow-2
Data Science: Bayesian Linear Regression in Python https://deeplearningcourses.com/c/bayesian-linear-regression-in-python
Data Science: Bayesian Classification in Python https://deeplearningcourses.com/c/bayesian-classification-in-python
Classical Statistical Inference and A/B Testing in Python https://deeplearningcourses.com/c/statistical-inference-in-python
Linear Programming for Linear Regression in Python https://deeplearningcourses.com/c/linear-programming-python
MATLAB for Students, Engineers, and Professionals in STEM https://deeplearningcourses.com/c/matlab
Data Science & Machine Learning: Naive Bayes in Python https://deeplearningcourses.com/c/data-science-machine-learning-naive-bayes-in-python
Cutting-Edge AI: Deep Reinforcement Learning in Python https://deeplearningcourses.com/c/cutting-edge-artificial-intelligence
Recommender Systems and Deep Learning in Python https://deeplearningcourses.com/c/recommender-systems
Machine Learning and AI: Support Vector Machines in Python https://deeplearningcourses.com/c/support-vector-machines-in-python
Deep Learning: Advanced Computer Vision https://deeplearningcourses.com/c/advanced-computer-vision
Deep Learning: Advanced NLP and RNNs https://deeplearningcourses.com/c/deep-learning-advanced-nlp
Deep Learning: GANs and Variational Autoencoders https://deeplearningcourses.com/c/deep-learning-gans-and-variational-autoencoders
Advanced AI: Deep Reinforcement Learning in Python https://deeplearningcourses.com/c/deep-reinforcement-learning-in-python
Artificial Intelligence: Reinforcement Learning in Python https://deeplearningcourses.com/c/artificial-intelligence-reinforcement-learning-in-python
Natural Language Processing with Deep Learning in Python https://deeplearningcourses.com/c/natural-language-processing-with-deep-learning-in-python
Deep Learning: Recurrent Neural Networks in Python https://deeplearningcourses.com/c/deep-learning-recurrent-neural-networks-in-python
Unsupervised Machine Learning: Hidden Markov Models in Python https://deeplearningcourses.com/c/unsupervised-machine-learning-hidden-markov-models-in-python
Deep Learning Prerequisites: The Numpy Stack in Python https://deeplearningcourses.com/c/deep-learning-prerequisites-the-numpy-stack-in-python
Deep Learning Prerequisites: Linear Regression in Python https://deeplearningcourses.com/c/data-science-linear-regression-in-python
Deep Learning Prerequisites: Logistic Regression in Python https://deeplearningcourses.com/c/data-science-logistic-regression-in-python
Data Science: Deep Learning and Neural Networks in Python https://deeplearningcourses.com/c/data-science-deep-learning-in-python
Cluster Analysis and Unsupervised Machine Learning in Python https://deeplearningcourses.com/c/cluster-analysis-unsupervised-machine-learning-python
Data Science: Supervised Machine Learning in Python https://deeplearningcourses.com/c/data-science-supervised-machine-learning-in-python
Bayesian Machine Learning in Python: A/B Testing https://deeplearningcourses.com/c/bayesian-machine-learning-in-python-ab-testing
Data Science: Natural Language Processing in Python https://deeplearningcourses.com/c/data-science-natural-language-processing-in-python
Modern Deep Learning in Python https://deeplearningcourses.com/c/data-science-deep-learning-in-theano-tensorflow
Ensemble Machine Learning in Python: Random Forest and AdaBoost https://deeplearningcourses.com/c/machine-learning-in-python-random-forest-adaboost
Deep Learning: Convolutional Neural Networks in Python https://deeplearningcourses.com/c/deep-learning-convolutional-neural-networks-theano-tensorflow
Unsupervised Deep Learning in Python https://deeplearningcourses.com/c/unsupervised-deep-learning-in-python