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Machine Learning Materials
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Simple Linear Regression_STAT-501
What is the "Best Fitting Line"?
Simple and Multiple Linear Regression in Python
Modeling and Prediction for Movies Data in R
Linear Regression in Python_Susan Li_with regression_Random forest_ Boosting
Linear Regression in Python_Susan Li_simple
A Friendly Introduction to Linear Regression_Luis Serrano
Machine Learning Tutorial Python - 4: Gradient Descent and Cost Function
linear regression with interaction
Ridge, Lasso and Elastic-Net Regression in R
Regularization of Linear Models with SKLearn
A Complete Tutorial on Ridge and Lasso Regression in Python
Polynomial Regression_STAT_501
Understand Power of Polynomials with Polynomial Regression
Python Implementation of Polynomial Regression
Machine Learning Fundamentals: The Confusion Matrix
Machine Learning Fundamentals: Sensitivity and Specificity
ROC and AUC, Clearly Explained!
Understanding Confusion Matrix
Beyond Accuracy: Precision and Recall
Performance Metrics for Classification problems in Machine Learning
Metrics To Evaluate Machine Learning Algorithms in Python
A Friendly Introduction to Logistic Regression and the Perceptron Algorithm_Luis Serrano
Building a Logistic Regression in Python
logit regression r data analysis examples
faq: how do i interpret odds ratios in logistic regression?
Building A Logistic Regression in Python, Step by Step
Logistic Regression - Analysis
StatQuest: Random Forests Part 1 - Building, Using and Evaluating
StatQuest: Random Forests in R
Decision Tree_entropy_calculation by hand_Saedsayad.com
Decision Tree from the Scratch_python
Analysis of Various Decision Tree Algorithms for Classification in Data Mining_paper_pdf
How To Implement The Decision Tree Algorithm From Scratch In Python
What is a Decision Tree? How does it work?
A Complete Tutorial on Tree Based Modeling from Scratch (in R & Python)
An Implementation and Explanation of the Random Forest in Python
Naive_bayes_calculation_by_hand_saedsayad.com
How To Implement Naive Bayes From Scratch in Python
Better Naive Bayes: 12 Tips To Get The Most From The Naive Bayes Algorithm
6 Easy Steps to Learn Naive Bayes Algorithm (with codes in Python and R)
Naive Bayes & SVM Spam Filtering_kaggle
Support Vector Machines (SVMs): A friendly introduction_Luis Serrano
Support Vector Machine - Classification (SVM)_saedsayad.com
Support Vector Machine detail analysis_kaggle
SVM with Scikit-Learn (SVM with parameter tuning_kaggle
K Nearest Neighbors - Regression_saedsayad
K Nearest Neighbors - Classification_saedsayad
StatQuest: K-nearest neighbors, Clearly Explained
A Practical Introduction to K-Nearest Neighbors Algorithm for Regression (with Python code)
K-nearest neighbors algorithm with code from scratch
A Comprehensive Guide to Ensemble Learning (with Python codes)
Machine Learning: Classification_by University of Washington_Adaboost
A Kaggle Master Explains Gradient Boosting
A Step by Step Gradient Boosting Example for Classification
A Step by Step Gradient Boosting Decision Tree Example
- Nice overview on different Clustering algorithm and Clustering perfomance evaluation at scikit-learn
StatQuest: Hierarchical Clustering-youtube
Hierarchical Agglomerative Clustering - Complete Linkage Clustering
Hierarchical Clustering with Python and Scikit-Learn
scikit-learn_implementation_medium
Expectation Maximization: how it works_youtube
In Depth: Gaussian Mixture Models
Gaussian Mixture Model_algorithm_python
my_exercise_from Udacity_github
my_exercise_from Udacity_nbviewer
StatQuest: Principal Component Analysis (PCA), Step-by-Step_youtube
Principal Component Analysis (PCA)_Luis Serrano
A tutorial on Principal Components Analysis_Lindsay_Smith
How to Calculate the Principal Component Analysis from Scratch in Python
Eigenvectors and eigenvalues_3Blue1Brown
A Gentle Introduction to Expected Value, Variance, and Covariance with NumPy
The Fundamental Difference Between Principal Component Analysis and Factor Analysis
In Depth: Principal Component Analysis
Practical Guide to Principal Component Analysis (PCA) in R & Python
Data Science with Python & R: Dimensionality Reduction and Clustering
Principal Component Analysis in R
Principal Component Methods in R: Practical Guide
Visualizing Multidimensional Data in Python_PCA_LDA
PCA, MDS, k-means, Hierarchical clustering and heatmap for microarray data
StatQuest: Linear Discriminant Analysis (LDA) clearly explained_youtube
Implementing LDA in Python with Scikit-Learn
StatQuest: t-SNE, Clearly Explained
Introduction to t-SNE_datacamp
Visualising high-dimensional datasets using PCA and t-SNE in Python
StatQuest: Probability vs Likelihood_youtube
StatQuest: Maximum Likelihood, clearly explained!!!
Bayesian inference for parameter estimation
Probability concepts explained: Maximum likelihood estimation
A Zero-Math Introduction to Markov Chain Monte Carlo Methods
Markov Chains_Explained Visually
What is the Difference Between a Batch and an Epoch in a Neural Network?
A Gentle Introduction to Mini-Batch Gradient Descent and How to Configure Batch Size
What is the Difference Between Test and Validation Datasets?
jupyter-notebook-tips-tricks-shortcuts
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