Pallavi Pandey
Grid Search in scikit-learn
The performance of our Machine Learning model is largely based on the hyperparameter values for the model. Hence, hyperparameter tuning…
Cross-Validation in scikit-learn
Cross-validation is a statistical method used in Machine Learning for estimating the performance of models. It is very important to…
Feature Scaling: MinMax, Standard and Robust Scaler
Feature Scaling is performed during the Data Preprocessing step. Also known as normalization, it is a method that is used…
XGBoost Algorithm using Python
XGBoost is one of the most popular boosting algorithms. It is well known to arrive at better solutions as compared…
Outlier Detection using Isolation Forests
For a dataset, an outlier is a data point that behaves differently from the other data points. Outliers cause huge…
Introduction to Ensemble Techniques: Bagging and Boosting
Ensemble Techniques are Machine Learning techniques that combine predictions from several models to give an optimal model. Several models are…
Dimensionality Reduction using tSNE
tSNE stands for t-distributed Stochastic Neighbor Embedding. It is a dimensionality reduction technique and is extremely useful for visualizing datasets…
Dimensionality Reduction using PCA
Dimensionality refers to the number of input variables (or features) of the dataset. Data with a large number of features…
Evaluating Clustering Methods
Predicting optimal clusters is of utmost importance in Cluster Analysis. For a given data, we need to evaluate which Clustering…
Spectral Clustering
Spectral Clustering is gaining a lot of popularity in recent times, owing to its simple implementation and the fact that…