Канал: IQmates

Python Code Discussion - Classification

Python Code Discussion - Classification

Python Code Discussion - Regression

Python Code Discussion - Regression

Explaining IQmates Gig

Explaining IQmates Gig

What exactly is IQmates?

What exactly is IQmates?

Can you answer today’s question?

Can you answer today’s question?

Waiting for a decision university admission? Here are 6 tips to make the most of that wait time.

Waiting for a decision university admission? Here are 6 tips to make the most of that wait time.

Did you get this one right?

Did you get this one right?

ChatGPT describing the Zulu Nation under Shaka (and creating interview questions)

ChatGPT describing the Zulu Nation under Shaka (and creating interview questions)

Complete Example of Lagrange's Principle

Complete Example of Lagrange's Principle

Tutorial part2

Tutorial part2

Tutorial part1

Tutorial part1

Lecture12

Lecture12

Lecture11 part2

Lecture11 part2

Comprehensive Example : Two Swinging Connected Rods

Comprehensive Example : Two Swinging Connected Rods

Lecture10 part2

Lecture10 part2

Lecture10 part1

Lecture10 part1

Lecture9 part2

Lecture9 part2

Calculus of Variations

Calculus of Variations

Examples : Moment of Intertia 3 (with Center of Mass)

Examples : Moment of Intertia 3 (with Center of Mass)

Examples : Moment of Intertia 2

Examples : Moment of Intertia 2

Examples : Moment of Inertia

Examples : Moment of Inertia

Moment of Inertia Tensor 2

Moment of Inertia Tensor 2

Moment of Inertia Tensor

Moment of Inertia Tensor

Detailed Recap and Moment of Inertia

Detailed Recap and Moment of Inertia

Example : Double Pendulum

Example : Double Pendulum

Conservative Forces and Potentials 4

Conservative Forces and Potentials 4

Conservative Forces and Potentials 3

Conservative Forces and Potentials 3

Conservative Forces and Potentials 2

Conservative Forces and Potentials 2

Conservative Forces and Potentials

Conservative Forces and Potentials

Applications of Lagrange's Principle 3

Applications of Lagrange's Principle 3

Applications of Lagrange's Principle 2

Applications of Lagrange's Principle 2

Applications of Lagrange's Equation 1

Applications of Lagrange's Equation 1

d'Alembert's Principle 2

d'Alembert's Principle 2

Deriving Lagrange's Equation 2

Deriving Lagrange's Equation 2

Deriving Lagrange's Equation 1

Deriving Lagrange's Equation 1

d'Alembert Principle 1

d'Alembert Principle 1

Equations of Constraint and Generalized Coordinates 3

Equations of Constraint and Generalized Coordinates 3

Equation of Motion of A Simple Pendulum

Equation of Motion of A Simple Pendulum

Equations of Constraint and Generalized Coordinates 2

Equations of Constraint and Generalized Coordinates 2

Transforming F=ma

Transforming F=ma

Forces and Equations of Constraint

Forces and Equations of Constraint

Singular Value Decomposition with Python Codes

Singular Value Decomposition with Python Codes

Kernel PCA with Python Codes

Kernel PCA with Python Codes

Incremental PCA in Python

Incremental PCA in Python

Sparse PCA in Python

Sparse PCA in Python

Principal Component Analysis in Python

Principal Component Analysis in Python

Loading the dataset

Loading the dataset

Introduction to Principal Component Analysis

Introduction to Principal Component Analysis

Principal Component Analysis Example

Principal Component Analysis Example

Back to MNIST dataset for Principal Component Analysis

Back to MNIST dataset for Principal Component Analysis

Principal Component Analysis

Principal Component Analysis

Scree Plots and How PCA Actually Reduces Dimension

Scree Plots and How PCA Actually Reduces Dimension

Introduction to Dimension Reduction

Introduction to Dimension Reduction

Better Evaluation Metrics Precision & Recall

Better Evaluation Metrics Precision & Recall

Using an ensemble to improve predictions

Using an ensemble to improve predictions

Model 4: LightGBM

Model 4: LightGBM

Evaluating on the Test Set

Evaluating on the Test Set

Model 2: Random Forest

Model 2: Random Forest

Model 3: XGBoost

Model 3: XGBoost

Better Evaluation Metrics ROC Curve and auROC

Better Evaluation Metrics ROC Curve and auROC

Introduction to the project

Introduction to the project

Model 1: Logistic Regression

Model 1: Logistic Regression

Data Acquisition and Exploration

Data Acquisition and Exploration

Cost function - Log Loss

Cost function - Log Loss

1.1. Linear Dimension Reduction Algorithms

1.1. Linear Dimension Reduction Algorithms

1.2. Manifold or Non Linear Dimension Reduction Algorithms

1.2. Manifold or Non Linear Dimension Reduction Algorithms

2 Clustering Unsupervised Learning Algorithms

2 Clustering Unsupervised Learning Algorithms

4 Anomaly Detection

4 Anomaly Detection

3 Feature Extraction Unsupervised Learning Algorithms

3 Feature Extraction Unsupervised Learning Algorithms

Using Unsupervised Learning to solve 6 challenges for data scientists

Using Unsupervised Learning to solve 6 challenges for data scientists

1 Dimension Reduction Algorithms

1 Dimension Reduction Algorithms

Some Unsupervised Learning Algorithms

Some Unsupervised Learning Algorithms

Introduction to Unsupervision Machine Learning

Introduction to Unsupervision Machine Learning

Supervised Learning vs Unsupervised Learning

Supervised Learning vs Unsupervised Learning

Elastic versus Inelastic Collisions

Elastic versus Inelastic Collisions

Potential Energy

Potential Energy

Conservation of Linear Momentum

Conservation of Linear Momentum

Linear Momentum

Linear Momentum

Power

Power

Work

Work

Example Work, Potential Energy and Friction

Example Work, Potential Energy and Friction

Principle of Conservation of Momentum

Principle of Conservation of Momentum

Kinetic Energy

Kinetic Energy

Example - Principle of Conservation of Momentum

Example - Principle of Conservation of Momentum

Question 3 Model Accuracy Clean

Question 3 Model Accuracy Clean

Question 2 Variable Selection Clean

Question 2 Variable Selection Clean

Question 1 - Is There a Relationship Between Response and Predictors

Question 1 - Is There a Relationship Between Response and Predictors

Pruning Decision Trees

Pruning Decision Trees

Predicting Using a Regression Decision Tree

Predicting Using a Regression Decision Tree

Regression Decision Trees

Regression Decision Trees

Introduction to Tree Based Methods

Introduction to Tree Based Methods

Principal Component Regression

Principal Component Regression

Introduction to Dimension Reduction Methods

Introduction to Dimension Reduction Methods

Scree Plots and How PCA Actually Reduces Dimension

Scree Plots and How PCA Actually Reduces Dimension

Principal Component Analysis Example

Principal Component Analysis Example

Principal Component Analysis

Principal Component Analysis

Lasso & Ridge Rigression using Mathematical Optimisation

Lasso & Ridge Rigression using Mathematical Optimisation

The Lasso Example

The Lasso Example

The Lasso

The Lasso

Ridge Regression Example

Ridge Regression Example

Introduction to Ridge Rigression

Introduction to Ridge Rigression

Introduction to Shrinkage Methods

Introduction to Shrinkage Methods

Validation Set and Cross Validation Estimates for Test Error

Validation Set and Cross Validation Estimates for Test Error

Adjusted R-Squared Estimate for Test Error

Adjusted R-Squared Estimate for Test Error

Bayesian Information Criterion (BIC) Estimate for Test Error

Bayesian Information Criterion (BIC) Estimate for Test Error

Akaike Information Criterion (AIC) Estimate for Test Error

Akaike Information Criterion (AIC) Estimate for Test Error

Cp Estimate for Test Error

Cp Estimate for Test Error

Model Selection Choosing the Optimal Model

Model Selection Choosing the Optimal Model

Backward Stepwise Selection Method

Backward Stepwise Selection Method

Forward Stepwise Selection Method

Forward Stepwise Selection Method

Best Subset Selection Method

Best Subset Selection Method

Introduction to Model Selection and Regularization

Introduction to Model Selection and Regularization

The Bootstrap Method

The Bootstrap Method

Cross Validation for Classification Settings

Cross Validation for Classification Settings

Method 3 - k-Fold Cross Validation

Method 3 - k-Fold Cross Validation

Method 2 - Leave One Out Cross Validation

Method 2 - Leave One Out Cross Validation

Method 1 - Validation Set Approach

Method 1 - Validation Set Approach

Introduction to Resampling Methods

Introduction to Resampling Methods

Quadratic Discriminant Analysis

Quadratic Discriminant Analysis

The ROC Curve

The ROC Curve

The Confusion Matrix, Sensitity and Specificity

The Confusion Matrix, Sensitity and Specificity

Linear Discriminant Analysis with More Predictors

Linear Discriminant Analysis with More Predictors

Linear Discriminant Analysis One Predictor Clean

Linear Discriminant Analysis One Predictor Clean

Bayes' Theorem of Classification

Bayes' Theorem of Classification

Introduction to Linear Discriminant Analysis (LDA)

Introduction to Linear Discriminant Analysis (LDA)

Multiple Logistic Regression

Multiple Logistic Regression

Making Predictions with Logistic Regression

Making Predictions with Logistic Regression

Estimating Logistic Regression Coefficients Maximum Likelihood Method

Estimating Logistic Regression Coefficients Maximum Likelihood Method

The Logistic Model

The Logistic Model

Introduction to Classification

Introduction to Classification

Why Linear Regression Will Not Work Perfectly In Classification

Why Linear Regression Will Not Work Perfectly In Classification

Introduction to Logistic Regression

Introduction to Logistic Regression

Problem #6 - Collinearity

Problem #6 - Collinearity

Problem #5 - High Leverage Points

Problem #5 - High Leverage Points

Problem #4 - Outliers

Problem #4 - Outliers

Problem #3 - Nonconstant Variance of Error Terms

Problem #3 - Nonconstant Variance of Error Terms

Problem #2 - Correlation of the Error Terms

Problem #2 - Correlation of the Error Terms

Problem #1 - Non linearity of the Data

Problem #1 - Non linearity of the Data

Including Non Linear Terms in Linear Models

Including Non Linear Terms in Linear Models

Including Interaction Terms in the Model (Non additive Linear Models)

Including Interaction Terms in the Model (Non additive Linear Models)

Dealing with Qualitative Variables

Dealing with Qualitative Variables

Estimating Multiple Linear Regression Coefficients

Estimating Multiple Linear Regression Coefficients

Multiple Linear Regression

Multiple Linear Regression

R- Squared Statistic

R- Squared Statistic

Residual Standard Error (RSE)

Residual Standard Error (RSE)

Assessing Simple Linear Model Accuracy

Assessing Simple Linear Model Accuracy

Estimating Model Coefficients: Simple Linear Regression

Estimating Model Coefficients: Simple Linear Regression

Hypothesis Test of Coefficient Estimates: Simple Linear Regression

Hypothesis Test of Coefficient Estimates: Simple Linear Regression

Accuracy of Coefficient Estimates: Simple Linear Regression

Accuracy of Coefficient Estimates: Simple Linear Regression

Introduction to Linear Regression

Introduction to Linear Regression

Confidence Intervals for Coefficient Estimates: Simple Linear Regression

Confidence Intervals for Coefficient Estimates: Simple Linear Regression

Classification Example K Nearest Neighbours KNN

Classification Example K Nearest Neighbours KNN

Assessing Model Accuracy Classification Setting

Assessing Model Accuracy Classification Setting

Bias Variance Trade Off

Bias Variance Trade Off

Assessing Model Accuracy - Measury of Quality of Fit

Assessing Model Accuracy - Measury of Quality of Fit

Regression versus Classification

Regression versus Classification

Supervised versus Unsupervised Learning

Supervised versus Unsupervised Learning

Model Prediction Accuracy and Model Interpretability Trade Off

Model Prediction Accuracy and Model Interpretability Trade Off

Parametric versus Non Parametric Methods Clean

Parametric versus Non Parametric Methods Clean

Modelling for prediction versus modelling for interference

Modelling for prediction versus modelling for interference

Introduction to Machine Learning

Introduction to Machine Learning

Weight

Weight

Force

Force

Inertia and Mass

Inertia and Mass

Newton's Law of Motion

Newton's Law of Motion

Motion Under Gravity

Motion Under Gravity

Examples - Equations of Motion

Examples - Equations of Motion

Equations of Motion

Equations of Motion

Acceleration

Acceleration

Velocity Time Graph

Velocity Time Graph

Distance Time Graph

Distance Time Graph

Vectors and Scalars

Vectors and Scalars

Motion in a Straight Line

Motion in a Straight Line

Introduction to High School Physics

Introduction to High School Physics

Mean Time and Sidereal Time Examples Part 2

Mean Time and Sidereal Time Examples Part 2

Mean Time and Sidereal Time Examples Part 1

Mean Time and Sidereal Time Examples Part 1

Geostationary Satillites

Geostationary Satillites

Mean Time and Sidereal Time

Mean Time and Sidereal Time

Apparent Solar Day and Sidereal Time Example

Apparent Solar Day and Sidereal Time Example

Apparent Solar Day and Sidereal Time

Apparent Solar Day and Sidereal Time

Sidereal Time, Hour Angle and Right Ascension cont) plus Examples

Sidereal Time, Hour Angle and Right Ascension cont) plus Examples

Sidereal Time, Hour Angle and Right Ascension

Sidereal Time, Hour Angle and Right Ascension

Sidereal Time and Sidereal Day

Sidereal Time and Sidereal Day

Example Right Ascension and Declination and Relationship Between RA and HA

Example Right Ascension and Declination and Relationship Between RA and HA

Right Ascension and Desclination

Right Ascension and Desclination

Second Equitorial System

Second Equitorial System

Example Hour Angle

Example Hour Angle

Example Declination

Example Declination

Hour Angle, Declination, Upper and Lower Transit

Hour Angle, Declination, Upper and Lower Transit

First Equitorial System

First Equitorial System

Azimuth - Altitude System and Relationship Between Altitude of Visible Pole and Latitude of Observer

Azimuth - Altitude System and Relationship Between Altitude of Visible Pole and Latitude of Observer

Altitude and Azimuth

Altitude and Azimuth

Vertical Coordinate System

Vertical Coordinate System

Celestial Sphere

Celestial Sphere

Examples Time and Angle Conversions

Examples Time and Angle Conversions

Example Longitude and Latitude and Time to Angle conversions

Example Longitude and Latitude and Time to Angle conversions

Latitude and Longitude

Latitude and Longitude

Geographical Equator and Greenwich Meridian as axes

Geographical Equator and Greenwich Meridian as axes

Great Circles and Axes

Great Circles and Axes

Introduction to Astronomy

Introduction to Astronomy