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Machine Learning
Machine Learning
Learning approach Variants
Parametric vs Non-Parametric Models
Common ML Pitfalls & How to Prevent Them
Bayesian Optimization
Hyperparameter Optimization
Optimization Techniques
Bias, Variance, and Their Trade-off
Correlation Analysis
Continous X
Discrete Numeric X
Binary X
Ordinal X
Categorical X
Linear Regression
Overview
Gradient Descent
Convergence Algorithm
Cost Functions
Multiple Linear Regression
Polynomial Regression
Performance Metrics
OLS
Bias–Variance Tradeoff
Hyperparameter Tuning in Linear Regression
Regularization & Generalization
Lasso Regression
Ridge Regression
Elastic Net Regression
Workflow of Regularized Regression
Cross-Validation
Hyperparameter Tuning methods
Handle Overfitting
Logistic Regression
Assumtpions
Intiution
Workflows
Cost Function
Performance Metrics
One-vs-Rest (OVR) Logistic Regression
Handling Imabalance dataset
Hyperparameter Tuning
Evaluation Metrics
Cross Validation
SVM
SVR
Cost Function
Evaluation Metrics
Hyper-Parameter Intiution
SVC
Cost Function
Evaluation Metrics
Hyper-paramter Tuning Intiution
Overview
Assumptions
Intiution
Workflows
Kernels
Naive Bayes
Assumptions
Intuition
Background
Workflows
Cost Functions
Performance Metrics
Variants of NB
Hyperparameter Tuning
K-Nearest Neighbors (KNN)
Assumptions
Intiution
Workflows
How to select cluster
\(k\)
KNN Variants
Cost Function
Performance Metrics
Hyperparameter Tuning
Regression & Classification
Decision Tree
Decision Tree Regressor
Cost Functions
Performance Metrics
Hyperparameter tuning
Decision Tree Classifier
Cost Function
Performance Metrics
Hyperparameters Tuning
Handle Underfitting/Overfitting
Assumptions
Purity Measures
Hyperparameter Tuning in Decision Tree
Random Forest
Ensembling
Assumptions
Intiution
Workflows
Out-of-Bag (OOB) Evaluation
Cost Function
Hyperparameter Tuning
AdaBoost (Adaptive Boosting)
Assumptions
Intiution
Workflow
Cost Function
Performance Metrics
AdaBoost Regressor
Hyperparameter Tuning
AdaBoost Classifier
Gradient Boosting
Assumptions
Intuition
Workflows
Gradient Boosting Classifier
Gradient Boosting Regressor
Cost Function
Hyperparameter Tuning
XGBoost
Assumptions
Intiution
Workflows
XGBoost Regressor
XGBoost Classifier
Cost Functions
Performance metrics
HyperParameter Tuning
K-Means Clustering
Assumptions
Intuition
Workflows
Cost Function
Performance Metrics
Hyperparameter tuning
K-Means from scratch
Hierarchical Clustering
Assumptions
Intiution
Workflow
Cost Function
Performance Metrics
Hyperparameter Tuning
PCA
Assumptions
Intiutions
Workflows
Hyperparameter Tuning
t-SNE
Assumptions
Intiution
Workflow
Cost Functions
Hyper Parameter Tuning
DBSCAN
Assumptions
Intiution
Workflows
Cost Function
Performance Metrics
Hyperparameter Tuning
Problem Statement
Silhouette Clustering
Anamoly Detection
Isolation Forest
Local Outlier Factor
NLP
NLP Applications
Terminologies
Part-of-Speech (POS)
Sentiment Analysis
Text Preprocessing
Tokenization
Stopwords
Stemming
Lemmatization
Handle Numbers in NLP
Handle Emojis & Emoticons
Spelling Corrections
Text Normalization
Vectorization
Bag of Words (BoW)
TF (Term Frequency)
TF-IDF
Word Embeddings
Repository
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