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TFIDF

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TFIDF

Machine Learning TFIDF

TFIDF

In this class, We discuss TFIDF.

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How to study Machine Learning @ Learning Monkey

Understanding Machine Learning with an Example

Understanding Different Types of Machine Learning with an Example

Point in a Coordinate System in Machine Learning with an Example

Understanding Equation of a Line Slope Intercept for Machine Learning

Graphical Intuition of Machine Learning with an Example

Understanding Plane and Hyperplane for Machine Learning with an Example

Derivative of a Function for Machine Learning

Finding the Maximum and Minimum of a Function for Machine Learning

Understanding Gradient Descent for Machine Learning with an Example

Mathematics behind Linear Regression

Mathematical Solution for Linear Regression in Machine Learning

Stochastic and Batch Gradient Descent in Machine Learning

Understanding Multiple Regression

Installing Python and Anaconda in Windows

How to do Data Cleaning in Machine Learning with an Example and Coding in Python

Amazon Mobile Review Data Set

How to Code Machine Learning

Data Cleaning Python Code on Amazon Review Data Set

Data Cleaning Cardio Data Set

Data Cleaning Python Code on Cardio Data Set

Min-Max Scaling Feature Scaling

Normalization Data Preprocessing

Mean Variance and Standard Deviation for Standardization

Standardization Feature Scaling

One Hot Encoding Feature Extraction

Stemming Data Preprocessing

Stop Words Data Preprocessing

Bag of Words Bigram and Ngram

Word2vec Example

Training Validation Testing Data

Data Preprocessing Code Cardio Data set

Data Preprocessing Code Amazon Data Set

Outliers and Noisy Data

Training Loss and Testing Loss

Overfitting Models with an Example

Underfitting Models with an Example

Types of Supervised Learning Algorithms with an Example

Calculating Accuracy in Classification

Calculating Accuracy in Regression RMSE

K Fold Cross Validation Understanding with an Example

Problem with Imbalanced Data

Confusion Matrix for Binary Classification

ROC Curve for Binary Classification

Intuition on Naive Bayes Classification in Machine Learning

Mathematics Basics Required for Naive Bayes

Understanding Naive Bayes Classification Algorithm Mathematics

Laplace Smoothing in Naive Bayes

Hyperparameter Underfitting and Overfitting in Naive Bayes

Log Probability Imbalanced Data Numerical Features in Naive Bayes

Multinomial Naive Bayes Code on Amazon Data set

Gaussian Naive Bayes Code on Cardio Data set

Introduction to K Nearest Neighbors KNN

How K Nearest Neighbors Use in Classification and Regression

Euclidean Manhattan and Minkowski Distance

Decision Surface K Nearest Neighbors

Hyperparameter Bias Variance Tradeoff in K nearest Neighbors

Weighted K Nearest Neighbour

Why Machine Learning Models Need Large Datasets

Curse of Dimensionality

Problem with K Nearest Neighbours

KNN Code on Amazon Mobile Dataset

KNN Code on Cardio Dataset

Coordinate Geometry Mathematics Basics and Terminology Required for Logistic Regression

Linear Algebra Basics Required for Logistic Regression

Sigmoid Function Logistic Regression

Introduction to Logistic Regression

Problem with Distance Measure in Logistic Regression

Loss Function Logistic Regression

Regularization in Logistic Regression

Hyperparameter Bias Variance Tradeoff in Logistic Regression

Solving Optimization Problem Logistic Regression

Logistic Regression Code on Amazon Dataset

Lagrange Multiplier Example for Understanding Support Vector Machine

Karush Kuhn Tucker Example for Understanding Support Vector Machine SVM

Primal and Dual problem for understanding Support Vector Machine SVM

Introduction to Support Vector Machine SVM Functional and Geometric Margin

Optimization Problem Support Vector Machine SVM

Solving Optimization Problem Support Vector Machine SVM

Use of Transforming Data to High Dimension

Kernel Function in Support Vector Machine SVM

Soft Margin Support Vector Machine SVM

Hyperparameter Bias Variance Tradeoff in Support Vector Machine SVM

Support Vector Machine Code on Amazon Mobile Data Set

Graphical Intuition on Decision Tree

Understanding Entropy Decision Tree

Information Gain in Decision Tree

Constructing Decision Tree

Gini Impurity in Decision Tree

Information Gain on Numerical Features Decision Tree

Hyperparameter Bias Variance Tradeoff Decision Tree

Decision Tree Graphviz Python Code on Amazon Data set

Word cloud Python Code on Amazon Dataset

Decision Tree Regression

Bagging Bootstrap Aggregation Random Forest Ensemble

Hyperparameter Bias Variance Tradeoff Random Forest

Random Forest Python Code on Amazon Mobile Dataset

Intuition on Gradient Boosting

Understanding Mathematics Behind Gradient Boosting

Pseudocode Gradient Boosting

Gradient Boosting Python Code on Amazon Mobile Dataset

Understanding and Implementing Stacking Ensemble on Amazon Dataset

K Means Clustering Unsupervised Learning

K Means ++ for Initialization

Knee or Elbow Method for Right K

Silhouette Method for Right K

K Means Clustering Failure Cases

K Means Clustering Implementation on Amazon Dataset

Introduction to Hierarchical Clustering Agglomerative and divisive

Agglomerative Clustering Example and Dendrogram

Similarity Measures Agglomerative Clustering

Agglomerative Clustering Code on Amazon Dataset

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