Course Materials
- Introduction to Machine Learning with Python
- Machine Learning in Action
- Machine Learning with TensorFlow
- Real World Machine Learning
- Hands On Machine Learning with ML.NET
Slides
- Understanding Big Picture
- Environment for Experiments
- Key Statistics
- Data Visualization
- Acquiring and Preparing Data
- Feature Engineering
- Machine Learning using Scikit Learn
- Supervised Machine Learning
- Unsupervised Machine Learning
- Introduction to Deep Learning
- Artificial Neural Network
- TensorFlow API
- Convolutional Neural Network (CNN)
- Recurrent Neural Network (RNN)
- Natural Language Processing (NLP)
- Conversational AI
Sample Data
AdventureWorks Sample Data
- Training
- Test
Sample Codes (right-click and save as)
- firstbook.ipynb
- numericpython.ipynb
- lemonade.ipynb
- plotting.ipynb
- beautiful.ipynb
- weatherforecast.ipynb
- read_text.ipynb
- iris.ipynb
- knn-classification.ipynb
- linear-classification.ipynb
- linear-regression.ipynb
- naive-bayes.ipynb
- decision-trees.ipynb
- kmeans-clustering.ipynb
- setuptf.ipynb
- beginner.ipynb
- classification.ipynb
- nltk-nlp.ipynb
- translator.ipynb
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