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Loss Function Logistic Regression

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  • Loss Function Logistic Regression
Machine Learning Loss Function Logistic Regression

Loss Function Logistic Regression

In this class, We discuss Loss Function Logistic Regression.

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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
TFIDF
Word2vec
Word2vec Example
Word2vec Code
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
Return to Machine Learning
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