Machine Learning with Python

By Dr. Maryam Rahbaralam

MY YOUTUBE TUTORIALS

• Regression model with Python: https://youtu.be/e0eyE4m238o
• Train/test split for regression and Cross-validation: https://youtu.be/Hpjgr3oholE
• Regularized regression and overfitting: https://youtu.be/VmxP7QTVh00
• Classification and K-Nearest Neighbours: https://youtu.be/ZbVPmjDaCFg
• Unsupervised Learning - Clustering: https://youtu.be/fqssd7g-mtY
• Principal component analysis(PCA): https://youtu.be/yFtpz54RGuA

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Content

First you need to install Jupyter Notebook

Installing Jupyter via Anaconda

Session 1:

31 July 2020

• Introduction to machine learning
• How to build a regression model with Python?

Code availabe at this link

Slides availabe at this link

Video available at this link

Session 2-1:

7 August 2020

• Train/test split for regression
• Cross-validation

Code availabe at this link

Slides availabe at this link

Video available at this link

Session 2-2:

7 August 2020

• Regularized regression
• Overfitting
• Ridge regression
• Lasso regression

Code availabe at this link

Slides availabe at this link

Video available at this link

Session 3:

14 August 2020

• Classification
• Feature scaling
• Confusion matrix
• K-Nearest Neighbours
• KNN classifier in Pyhton

Code availabe at this link

Slides availabe at this link

Video available at this link

Session 4:

21 August 2020

• Unsupervised Learning-1 - Clustering
• K-Means Clustering
• Elbow Method
• SpectralClustering estimator
• MiniBatchKMeans
• K-means for color compression¶

Code availabe at this link

Slides availabe at this link

Video available at this link

Session 5:

28 August 2020

• Principal component analysis (PCA)
• Dimensionality reduction
• COVARIANCE MATRIX
• Singular Value Decomposition (SVD)
• PCA in Python

Code availabe at this 1 and 2

Slides availabe at this link

Video available at this link