Intro to Machine Learning
- Introduction to Machine Learning
- Python for machine learning
- Making predictions with Machine Learning
- Handle outliers in regression - RANSC method
- Top 20 Classification algorithms
- Model fitting in Machine learning
- Linear Regression Algorithm
- KNN algorithm
- Decision Trees Algorithm
- Random Forest Algorithm
- n_estimators in random forest
- Visualize Random Forest
- Handle imbalanced data
- SVM algorithm
- Popular Boosting algorithms
- Confusion Matrix
- 12 ways to analyze Stock market
- Isolation Forest algorithm
- Random state in machine learning
- Sklearn feature selectors
Advance Machine Learning
- Principal component Analysis
- AdaBoost algorithm
- Gradient Boosting Algorithm
- XGBoost algorithm
- LIghtGBM algorithm
- CatBoost Algorithm
- Handle outliers in Machine Learning
- Facebook Prophet algorithm
- ARIMA for time series
- Extra trees algorithm
- Semi-supervised learning
- K-means clustering in Python
- Categorical encoding in pandas
- Sklearn one hot encoder
- Sklearn label encoding
- Sklearn standardscaler
- Sklearn minmaxscaler
- Sklean splitting function
- GridSearchCV
- Acta Materilia Machine Learning