Predicting Wine Quality Using MultiLayer Perceptron Classifier

Building H20 DRF Model for Bike Sharing

Saving RF Model on Type of Fault in Steel Plates

Spam Detection Using TFIDF

Building Linear Regression Model for Farmers Market

Building GBT Regression Model for Bike Sharing

Profiling Telco Churn Data

Building Model Using Decision Tree Classifier for Telco Churn

Analyzing Correlation and Summary Statistics for Housing Data

Building Model Using RFC for Telco Churn

Developing H20 RFC Model for Telco Churn

Building H20 K-means Cluster for Bike Sharing Data

Analyzing Telco Churn Data

Building K-means Cluster for Housing Data

Predicting Click-through with GBT Boosting

Building Spark-ML Pipeline Model on Spam Data

Predicting Acceleration Of Car Models Using Linear Regression

Predicting Spam and Evaluating Model

Training XGBoost Model on IRIS Data

Building Neural Network Regression Model for Bike Sharing Data

Building GBT Regression Model for Car Data

Performing Feature Selection and Importance in WHO Data Analysis

Building Decision Tree Regression Model on Car Data

Building K-means Cluster Model on Housing Data

Demonstrating Parameter Passing Process on Employment Data

Performing Chi-Square Test for Feature Selection

Building RFC & Logistic Regression Model for Churn Prediction

Performing Comprehensive Sales Data Analysis with Various Models

Generating Covariance and Correlation Matrix on Housing Data

Generating Cross Tab Matrix on Housing Data

Performing Dimensionality Reduction Using PCA on Housing Data

Exploring Housing Data

Analysing and Decomposition of Bike Sharing Features

Building H20 DRF Models on Bike Sharing Data

Building H2O GBM Model on Bike Sharing Data

Building H20 GLM Model

Building H2O GLRM Model on Credit Card Fraud Data

Building H20 Isolation Forest Model on Credit Card Fraud Data

Building H20 K-means Model on Bike Sharing Data

Building H20 Neural Network Model

Buidling H20 XGBoost Model on UCI Credit Card Data

Building Linear Regression Model on Household Power Consumption Data

Building K-means Cluster Model on Housing Data

Building RFC Model for Predicting House Price

Building Logistic Regression Model for SMS Spam Detection

Building H20 Isolation Forest Model for Anomaly Detection

Buidling Linear Regression Model for Storewise Retail Stock Prediction

Building Logistic Regression Model for Credit Card Fraud Prediction

Imputing Null Values with Mean, Median & Constant

Reading CSV and JSON File

Detecting Outlier for Housing Data

Detecting Diabetes Using Logistic Regression Model

Detecting Diabetes Using Logistic Regression Model

Processing Housing Data

Scaling Features Using Standard And Min Max Scaler

Identifying Skewness in Housing Data

Splitting Dataset Using Stratified Sampling

Handling Categorical Data with String Indexer and OneHotEncoder

Sampling Housing Data Using Standard Split Method

Performing Data Profiling on Bike Sharing Data

Validating Data Using Cross Validator

Cleaning and Generating Features in NFL Data

Implementing Sagemaker XGBoost

Applying SMOTE Oversampling to Address Imbalanced Data

Implementing SparkML Pipeline

Improving Spam Detection with Hyperparameter Tuning

Predicting House Price Using XGBoost Regression Model

Predicting Defects in Steel Plates Using Random Forest Classifier

Predicting Weekly Sales Using Random Forest Regression Model

Selecting Churn Prediction Model Using Grid Search & Cross-Validation

Normalizing Housing Data

Building Perceptorn Network on Iris Data