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Title: GitHub - PythonNorte/ml_course: This repository belongs to the course of machine learning with Python which is getting ready for AUT · GitHub

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1. Introduction to Pythonhttps://github.com/AmirMardan/ml_course/blob/main/1_intro_to_python/0_intro_to_python.ipynb
https://github.com/PythonNorte/ml_course#1-introduction-to-python
https://github.com/PythonNorte/ml_course#11-general-programming
1.2 Modular programminghttps://github.com/AmirMardan/ml_course/blob/main/1_intro_to_python/1_modular_programming.ipynb
https://github.com/PythonNorte/ml_course#12-modular-programming
2. Introduction to NumPyhttps://github.com/AmirMardan/ml_course/blob/main/2_numpy/0_intro_to_numpy.ipynb
https://github.com/PythonNorte/ml_course#2-introduction-to-numpy
https://github.com/PythonNorte/ml_course#3-data-manipulation-with-pandas
3.1 Introduction to pandashttps://github.com/AmirMardan/ml_course/blob/main/3_pandas/0_intro_to_pandas.ipynb
https://github.com/PythonNorte/ml_course#31-introduction-to-pandas
3.2 Data manipulation in using pandashttps://github.com/AmirMardan/ml_course/blob/main/3_pandas/1_data_manipulation_using_pandas.ipynb
https://github.com/PythonNorte/ml_course#32-data-manipulation-in-using-pandas
https://github.com/PythonNorte/ml_course#4-visualization
4.1 Matplotlibhttps://github.com/AmirMardan/ml_course/blob/main/4_visualization/0_matplotlib.ipynb
https://github.com/PythonNorte/ml_course#41-matplotlib
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https://github.com/PythonNorte/ml_course#42-seaborn
https://github.com/PythonNorte/ml_course#5-data-analysis-and-processing
5.1 Exploratory data analysis (EDA)https://github.com/AmirMardan/ml_course/blob/main/5_data_analysis_processing/0_introduction_to_EDA.ipynb
https://github.com/PythonNorte/ml_course#51-exploratory-data-analysis-eda
5.2 Data preparationhttps://github.com/AmirMardan/ml_course/blob/main/5_data_analysis_processing/1_intro_to_data_preparation.ipynb
https://github.com/PythonNorte/ml_course#52-data-preparation
5.3 Data Cleaninghttps://github.com/AmirMardan/ml_course/blob/main/5_data_analysis_processing/2_data_cleaning.ipynb
https://github.com/PythonNorte/ml_course#53-data-cleaning
5.4 Data Transformshttps://github.com/AmirMardan/ml_course/blob/main/5_data_analysis_processing/3_data_transform.ipynb
https://github.com/PythonNorte/ml_course#54-data-transforms
https://github.com/PythonNorte/ml_course#6-classical-machine-learning
6.1 Introduction to Machine Learninghttps://github.com/AmirMardan/ml_course/blob/main/6_classical_machine_learning/0_Intro_to_ML.md
https://github.com/PythonNorte/ml_course#61-introduction-to-machine-learning
6.2 Introduction to Scikit-Learnhttps://github.com/AmirMardan/ml_course/blob/main/6_classical_machine_learning/1_intro_to_sklearn.ipynb
https://github.com/PythonNorte/ml_course#62-introduction-to-scikit-learn
6.3 Regression 1https://github.com/AmirMardan/ml_course/blob/main/6_classical_machine_learning/2_regression_1.ipynb
https://github.com/PythonNorte/ml_course#63-regression-1
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6.5 Clustering 1https://github.com/AmirMardan/ml_course/blob/main/6_classical_machine_learning/4_clustering_1.ipynb
https://github.com/PythonNorte/ml_course#65-clustering-1
https://github.com/PythonNorte/ml_course#7-fully-connected-neural-networks-fcnns
7.1 Introduction to TensorFlowhttps://github.com/AmirMardan/ml_course/blob/main/7_fully_connected_nn/0_intro_to_tensorflow.ipynb
https://github.com/PythonNorte/ml_course#71-introduction-to-tensorflow
7.2 Introduction To Fully Connected Neural Networkshttps://github.com/AmirMardan/ml_course/blob/main/7_fully_connected_nn/1_intro_to_NN.ipynb
https://github.com/PythonNorte/ml_course#72-introduction-to-fully-connected-neural-networks
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