Multi-Class Classification

How to implement Random Forest Algorithm with Python and Scikit-Learn

Hits: 34  How to implement Random Forest Algorithm with Python and Scikit-Learn Random forest is a type of supervised machine learning algorithm based on ensemble learning. Ensemble learning is a type of learning where you join different types of algorithms or same algorithm multiple times to form a more powerful prediction model. The random forest algorithm combines multiple …

How to implement K-Nearest Neighbors Algorithm in Python and Scikit-Learn

Hits: 20  How to implement K-Nearest Neighbors Algorithm in Python and Scikit-Learn The K-nearest neighbors (KNN) algorithm is a type of supervised machine learning algorithms. KNN is extremely easy to implement in its most basic form, and yet performs quite complex classification tasks. It is a lazy learning algorithm since it doesn’t have a specialized training phase. …

How to do Binary Classification: Larger Keras Model in Python with Standardized data

Hits: 18 (How to do Binary Classification: Keras Model in Python with Standardized data)   Python Example for Beginners Special 95% discount 2000+ Applied Machine Learning & Data Science Recipes Portfolio Projects for Aspiring Data Scientists: Tabular Text & Image Data Analytics as well as Time Series Forecasting in Python & R Two Machine Learning …

How to write a program to classify Image using Keras and Python

Hits: 119 (End-to-End Jupyter Notebook for Citizen Data Scientist & Business Analyst) Write a program to classify Image using Keras and Python. In this end-to-end applied machine learning and data science notebook, the reader will learn: How to write a program to classify Image using Keras and Python. Download   How to write a program …

Write a program to predict mobile price using XGBoost with Monte Carlo Cross Validation in Python

Hits: 79 (End-to-End Jupyter Notebook for Citizen Data Scientist & Business Analyst) Write a program to predict mobile price using XGBoost with Monte Carlo Cross Validation in Python. In this end-to-end applied machine learning and data science notebook, the reader will learn: How to predict mobile price using XGBoost with Monte Carlo Cross Validation in …

Write a program to predict mobile price using XGBoost with Grid Search Cross Validation in Python

Hits: 180 (End-to-End Jupyter Notebook for Citizen Data Scientist & Business Analyst) Write a program to predict mobile price using XGBoost with Grid Search Cross Validation in Python. In this end-to-end applied machine learning and data science notebook, the reader will learn: How to predict mobile price using XGBoost with Grid Search Cross Validation in …

Write a program to predict mobile price using Random Forest Classifier with Monte Carlo CV in Python

Hits: 45 (End-to-End Jupyter Notebook for Citizen Data Scientist & Business Analyst) Write a program to predict mobile price using Random Forest Classifier with Monte Carlo CV in Python. In this end-to-end applied machine learning and data science notebook, the reader will learn: How to predict mobile price using Random Forest Algorithm with Monte Carlo …

Write a program to predict mobile price using Decision Tree with Grid Search CV in Python

Hits: 99 (End-to-End Jupyter Notebook for Citizen Data Scientist & Business Analyst) Write a program to predict mobile price using Decision Tree with Grid Search CV in Python. In this end-to-end applied machine learning and data science notebook, the reader will learn: How to predict mobile price using Decision Tree with Grid Search CV in …

Machine Learning Classification in R using Support Vector Machine with IRIS Dataset

Hits: 318   In this Applied Machine Learning & Data Science Recipe (Jupyter Notebook), the reader will find the practical use of applied machine learning and data science in R programming: Machine Learning Classification in R using Support Vector Machine with IRIS Dataset. What should I learn from this Applied Machine Learning & Data Science …

Machine Learning Classification in R | Quadratic Discriminant Analysis | Data Science for Beginners

Hits: 163  In this Applied Machine Learning & Data Science Recipe (Jupyter Notebook), the reader will find the practical use of applied machine learning and data science in R programming: Machine Learning in R | Classification | Data Science for Beginners | IRIS | LDA | CARET tutorials. What should I learn from this Applied …

Machine Learning in R | Classification | Data Science for Beginners | IRIS | LDA | CARET tutorials

Hits: 216   In this Applied Machine Learning & Data Science Recipe (Jupyter Notebook), the reader will find the practical use of applied machine learning and data science in R programming: Machine Learning in R | Classification | Data Science for Beginners | IRIS | LDA | CARET tutorials. What should I learn from this …

Machine Learning and Data Science in Python using XGBoost with Ames Housing Dataset | Pandas | MySQL

Hits: 107   In this Applied Machine Learning & Data Science Recipe (Jupyter Notebook), the reader will find the practical use of applied machine learning and data science in R programming: Machine Learning and Data Science in Python using XGBoost with Ames Housing Dataset. What should I learn from this Applied Machine Learning & Data …

Machine Learning with Abalone Dataset in R | Practical Data Science tutorials with R for Beginners and Citizen Data Scientists

Hits: 179   In this Applied Machine Learning & Data Science Recipe (Jupyter Notebook), the reader will find the practical use of applied machine learning and data science in R programming: Machine Learning with Abalone Dataset in R. What should I learn from this Applied Machine Learning & Data Science tutorials? You will learn: Machine …

Boosting ensembles with depth parameter tuning using yeast dataset in Python

Hits: 60    In this Applied Machine Learning & Data Science Recipe (Jupyter Notebook), the reader will find the practical use of applied machine learning and data science in Python programming: How to compare boosting ensemble Classifiers in Multiclass Classification. What should I learn from this recipe? You will learn: How to install, load and …

How to compare boosting ensemble Classifiers in Multiclass Classification

Hits: 104    In this Applied Machine Learning & Data Science Recipe (Jupyter Notebook), the reader will find the practical use of applied machine learning and data science in Python programming: How to compare boosting ensemble Classifiers in Multiclass Classification. What should I learn from this recipe? You will learn: How to install, load and …