FreeCourseWeb Udemy Machine Learning Intro for Python Developers

/2. First Program (Classifier)/

3. First Program (Classifier).mp4

1. Installing Scikit and Numpy.html

2. Important Note.html

3. First Program (Classifier).vtt

3.1 ML-classification-example1.py.py

4. Lecture Notes.html

4.1 ML-classification-example1.py.py

5. Exercise.html

5.1 solution.py.py

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/1. Introduction/

1. Introduction.mp4

1. Introduction.vtt

2. What is Machine Learning.mp4

2. What is Machine Learning.vtt

3. Example Problems.mp4

3. Example Problems.vtt

4. Supervised Learning.mp4

4. Supervised Learning.vtt

/3. Iris Classifier/

1. Iris Classifier.mp4

1. Iris Classifier.vtt

1.1 ML-classification-iris.py.py

2. Accuracy Score.mp4

2. Accuracy Score.vtt

2.1 ML-accuracy.py.py

3. See a Decision Tree.mp4

3. See a Decision Tree.vtt

3.1 ML-draw-a-classification-tree.py.py

/4. Regression/

1. Linear Regression.mp4

1. Linear Regression.vtt

1.1 ML-regression1.py.py

1.2 ML-regression2.py.py

2. Lecture Notes.html

3. Regression Example.mp4

3. Regression Example.vtt

3.1 ML-regression3.py.py

4. Polynomial Regression.mp4

4. Polynomial Regression.vtt

4.1 ML-nonlinear-prediction.py.py

/5. Clustering/

1. Clustering.mp4

1. Clustering.vtt

1.1 ML-cluster.py.py

2. Lecture Notes.html

3. Kmeans explained.mp4

3. Kmeans explained.vtt

Total files 47