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input
input
 
 
notes
notes
 
 
references
references
 
 
.gitignore
.gitignore
 
 
Exercise 1 Python Exercises.ipynb
Exercise 1 Python Exercises.ipynb
 
 
Exercise 2 Database Access.ipynb
Exercise 2 Database Access.ipynb
 
 
Exercise 3 Customer Segmentation using Clustering.ipynb
Exercise 3 Customer Segmentation using Clustering.ipynb
 
 
Iris.csv
Iris.csv
 
 
Lecture 1 Language Introduction-ModifiedDay1.ipynb
Lecture 1 Language Introduction-ModifiedDay1.ipynb
 
 
Lecture 1 Language Introduction.ipynb
Lecture 1 Language Introduction.ipynb
 
 
Lesson 2 Database Access-ModifiedDay1.ipynb
Lesson 2 Database Access-ModifiedDay1.ipynb
 
 
Lesson 2 Database Access.ipynb
Lesson 2 Database Access.ipynb
 
 
Lesson 3 K-Means Clustering.ipynb
Lesson 3 K-Means Clustering.ipynb
 
 
Lesson 4 Hierarchical Clustering.ipynb
Lesson 4 Hierarchical Clustering.ipynb
 
 
Lesson 5 DBSCAN Clustering.ipynb
Lesson 5 DBSCAN Clustering.ipynb
 
 
Lesson 6a Simple Data Cleansing Using Titanic Data.ipynb
Lesson 6a Simple Data Cleansing Using Titanic Data.ipynb
 
 
Lesson 6b Feature Engineering Example using Titanic Data.ipynb
Lesson 6b Feature Engineering Example using Titanic Data.ipynb
 
 
Lesson 6c Scatter Plot and Correlation.ipynb
Lesson 6c Scatter Plot and Correlation.ipynb
 
 
Lesson 7 Dimensionality Reduction.ipynb
Lesson 7 Dimensionality Reduction.ipynb
 
 
Lesson 8 Simple Artificial Neural Network.ipynb
Lesson 8 Simple Artificial Neural Network.ipynb
 
 
Lesson 8b Using a Trained Deep Learning Neural Network.ipynb
Lesson 8b Using a Trained Deep Learning Neural Network.ipynb
 
 
Lesson 9 Text Processing.ipynb
Lesson 9 Text Processing.ipynb
 
 
Lesson_10_Transfer_Learning.ipynb
Lesson_10_Transfer_Learning.ipynb
 
 
README.md
README.md
 
 
Solution 1 Python Exercises.ipynb
Solution 1 Python Exercises.ipynb
 
 
Solution 2 Database Access.ipynb
Solution 2 Database Access.ipynb
 
 
Style_Transfer_Example.ipynb
Style_Transfer_Example.ipynb
 
 
plot_iris_dataset.ipynb
plot_iris_dataset.ipynb
 
 

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Repository for Python and Machine Learning

How to use

  • Go to a folder where you wanto to download this project to and type:
git clone https://github.com/sa48/Python.git
  • Afterwards you can run Jupyter Notebook in the python folder.
cd Python
jupyter notebook

The lessons and exercises will be updated everyday and you should do an update by issuing this command:

git pull

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