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Course Content
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Course Introduction
00:00
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Welcome
00:00
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Introduction to Machine Learning
00:00
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Python for Machine Learning
00:00
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Supervised vs Unsupervised
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Graded Quiz: Intro to Machine Learning
00:00
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Practice Quiz: Intro to Machine Learning
00:00
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Introduction to Regression
00:00
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Simple Linear Regression
00:00
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Model Evaluation in Regression Models
00:00
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Evaluation Metrics in Regression Models
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Multiple Linear Regression
00:00
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Graded Quiz: Regression
00:00
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Practice Quiz: Regression
00:00
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Lab: Simple Linear Regression
00:00
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Lab: Multiple Linear Regression
00:00
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Introduction to Classification
00:00
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K-Nearest Neighbours
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Evaluation Metrics in Classification
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Introduction to Decision Trees
00:00
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Building Decision Trees
00:00
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Graded Quiz: Classification
00:00
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Practice Quiz: Classification
00:00
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Lab: KNN
00:00
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Lab: Decision Trees
00:00
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(Optional) Lab: Faster Credit Card Fraud Detection using Snap ML
00:00
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Lab: Regression Trees
00:00
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(Optional) Lab: Faster Taxi Tip Prediction using Snap ML
00:00
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Intro to Logistic Regression
00:00
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Logistic regression vs Linear regression
00:00
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Logistic Regression Training
00:00
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Support Vector Machine
00:00
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Multiclass Prediction
00:00
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Graded Quiz: Linear Classification
00:00
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Practice Quiz: Linear Classification
00:00
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Lab: Logistic Regression
00:00
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Lab: SVM (Support Vector Machines)
00:00
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Lab: Multiclass Prediction
00:00
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Intro to Clustering
00:00
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Intro to k-Means
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More on k-Means
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Graded Quiz: Clustering
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Practice Quiz: Clustering
00:00
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In this module, you will do a project based of what you have learned so far. You will submit a report of your project for peer evaluation.
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