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├── README.md
└── Supervised Machine Learning: Regression and Classification
    ├── Week 1: Introduction to Machine Learning
    │   ├── 1. Overview of Machine Learning
    │   │   ├── 1. Welcome to machine learning!.txt
    │   │   └── 2. Applications of machine learning.txt
    │   ├── 2. Supervised vs. Unsupervised Machine Learning
    │   │   ├── 1. What is Machine Learning.txt
    │   │   ├── 2._01_examples_of_supervised_machine_learning_alogrithm_applications_in_real_world.png
    │   │   ├── 2._02_examples_of_housing_price_prediction_using_regression.png
    │   │   ├── 2. Supervised Learning Part 1.txt
    │   │   ├── 3._01_examples_breast_cancer_detection.png
    │   │   ├── 3._02_examples_breast_cancer_detection_2_or_more_input.png
    │   │   ├── 3._03_summary_of_supervised_learning.png
    │   │   ├── 3. Supervised Learning Part 2.txt
    │   │   ├── 4._01_difference_between_supervised_and_unsupervised_learning.png
    │   │   ├── 4._02_usage_of_clustring_in_dna_analysis.png
    │   │   ├── 4._03_usage_of_clustring_in_market_segmentation.png
    │   │   ├── 4. UnSupervised Learning Part 1.txt
    │   │   ├── 4. UnSupervised Learning Part 2.txt
    │   │   └── 5. Jupyter Notebooks.txt
    │   ├── 3. Practice Quiz: Supervised vs unsupervised learning
    │   │   └── 1._practise_quiz_supervised_vs_unsupervised_learning.png
    │   ├── 4. Regression Model
    │   ├── 5. Practise Quiz: Regression Model
    │   ├── 6. Train Model with Gradient Descent
    │   ├── 7. Practise Quiz: Train Model with Gradient Descent
    │   └── Optional Labs
    │       ├── C1_W1_Lab01_Python_Jupyter_Soln.ipynb
    │       ├── C1_W1_Lab03_Model_Representation_Soln.ipynb
    │       ├── C1_W1_Lab04_Cost_function_Soln.ipynb
    │       ├── C1_W1_Lab05_Gradient_Descent_Soln.ipynb
    │       ├── data.txt
    │       ├── deeplearning.mplstyle
    │       ├── images
    │       │   ├── C1W1L1_Markdown.PNG
    │       │   ├── C1W1L1_Run.PNG
    │       │   ├── C1W1L1_Tour.PNG
    │       │   ├── C1_W1_L3_S1_Lecture_b.png
    │       │   ├── C1_W1_L3_S1_model.png
    │       │   ├── C1_W1_L3_S1_trainingdata.png
    │       │   ├── C1_W1_L3_S2_Lecture_b.png
    │       │   ├── C1_W1_L4_S1_Lecture_GD.png
    │       │   ├── C1_W1_Lab02_GoalOfRegression.PNG
    │       │   ├── C1_W1_Lab03_alpha_too_big.PNG
    │       │   ├── C1_W1_Lab03_lecture_learningrate.PNG
    │       │   └── C1_W1_Lab03_lecture_slopes.PNG
    │       ├── lab_utils_common.py
    │       └── lab_utils_uni.py
    ├── Week 2: Regression with multiple input variables
    └── Week 3: Classification