Course Content
Course Introduction
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The Role of Machine Learning in Career Development
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The Artificial Intelligence Family Tree
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System Requirements
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Prerequisites
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Course Overview
Machine Learning Basics
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Introduction to Machine Learning
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Understanding Classification and Regression
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Comparing Supervised and Unsupervised Learning
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Getting Ready to Explore Machine Learning
Python Programming Basic
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UPLOAD THE FIRST MODULE IN PYTHON PROGRAMMING FOR DATA ANALYSIS
Data Processing and Visualization Technique
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Pandas: Overview and Installation Procedures
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Core Concepts of DataFrames
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Reading and Writing Excel and CSV Files
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Techniques for Managing Missing Data – I
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Techniques for Managing Missing Data – II
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Data Aggregation and Grouping Methods
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Dataset Integration: Concatenation and Merging
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Data Visualization Using Matplotlib and Seaborn
Supervision Machine Learning : Regression
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Basic Linear Regression
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Multiple Regression
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Quiz
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Exercise
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Loss Function
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Derivatives & Partial Derivatives
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Chain Rule
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Quiz
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Exercise
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Gradient Descent (Concept)
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Gradient Descent (Python)
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Why MSE Instead of MAE
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Model Evaluation: Train–Test Split
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Model Evaluation Metrics
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Quiz
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Exercise
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One-Hot Encoding
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Quiz
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Polynomial Regression
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Quiz
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Exercise
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Overfitting vs Underfitting
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Causes & Fixes for Overfitting/Underfitting
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L1/L2 Regularization
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Bias–Variance Tradeoff
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Quiz
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Exercise
Supervision Machine Learning : Classification
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BasiIntroduction to Classification
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Logistic Regression for Binary Classification
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Evaluation Metrics: Accuracy, Precision, Recall
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Quiz
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Exercise
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Evaluation Metrics: F1 Score and Confusion Matrix
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Logistic Regression for Multiclass Problems
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Log Loss (Cost Function)
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Quiz
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Exercise
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Support Vector Machines (SVM)
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Data Preprocessing: Feature Scaling
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Scikit-learn Pipelines
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Quiz
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Exercise
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Naive Bayes: Concepts
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Naive Bayes: SMS Spam Detection
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Quiz
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Exercise
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Decision Trees: Concepts
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Decision Trees: Salary Prediction
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Quiz
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Exercise
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Class Imbalance: Understanding the Problem
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Class Imbalance Handling with imblearn (Churn Prediction)
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Quiz
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Exercise
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