Your Learning Progress

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Probability and Statistics

Master Probability and Statistics fundamentals

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Data Visualization

Master Data Visualization fundamentals

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Data Scaling

Master Data Scaling fundamentals

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Linear Regression

Master Linear Regression fundamentals

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Loss Functions

Master Loss Functions fundamentals

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Gradient Descent

Master Gradient Descent fundamentals

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Logistic Regression

Master Logistic Regression fundamentals

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Regularization

Master Regularization fundamentals

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Over/Under Fitting

Master Over/Under Fitting fundamentals

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Performance Metrics

Master Performance Metrics fundamentals

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Decision Trees

Master Decision Trees fundamentals

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K-Nearest Neighbors (KNN)

Master K-Nearest Neighbors (KNN) fundamentals

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Support Vector Machines (SVM)

Master Support Vector Machines (SVM) fundamentals

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Perceptron

Master Perceptron fundamentals

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Activation Functions

Master Activation Functions fundamentals

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Multilayer Perceptrons

Master Multilayer Perceptrons fundamentals

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Reinforcement Learning

Master Reinforcement Learning fundamentals

🔬 Projects

0/5

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The XOR Problem

Complete hands-on ML project

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Iris Flower Classification

Complete hands-on ML project

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Boston Housing Problem

Complete hands-on ML project

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Movie Recommendation System

Complete hands-on ML project

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Handwritten Digit Recognition

Complete hands-on ML project

📝 Quizzes

0/9

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Linear Algebra and Probability

Test your understanding of linear algebra and probability concepts.

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Data Preparation and Visualization

Evaluate your knowledge on data visualization and scaling.

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Linear Models and Optimization

Explore linear regression, loss functions, and gradient descent.

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Advanced Regression Concepts

Understand logistic regression, regularization, and overfitting.

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Evaluation Metrics

Assess your understanding of performance metrics in ML.

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Tree-Based and Distance-Based Models

Learn about decision trees and K-Nearest Neighbors (KNN).

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Support Vector Machines

Delve into the fundamentals of support vector machines (SVM).

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Neural Networks Basics

Understand perceptrons, activation functions, and multilayer perceptrons.

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Reinforcement Learning

Test your knowledge of reinforcement learning principles.