Keras and Tensorflow with Grid Search Cross Validation | IRIS Data Keras and TensorFlow are two powerful libraries that are used for building and training machine learning models. Keras is a high-level neural networks API, written in Python, that runs on top of TensorFlow. It is designed to make it easy to build and train …
SKLEARN XGBoost Classifier with Grid Search Cross Validation XGBoost is a powerful and efficient implementation of the Gradient Boosting algorithm that is used to classify items into different categories. It is an ensemble method that combines the predictions of multiple weak models, such as decision trees, to make a final prediction. The technique uses …
SKLEARN Gradient Boosting Classifier with Monte Carlo Cross Validation Gradient Boosting Classifier is a machine learning technique used to classify items into different categories. It is an ensemble method that combines the predictions of multiple weak models, such as decision trees, to make a final prediction. The technique uses an iterative process where each …
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: IRIS Flower Classification using SKLEARN RandomForest Classifier with Monte Carlo Cross Validation. Personal Career & Learning Guide for Data Analyst, Data Engineer and Data Scientist …
IRIS Flower Classification using SKLEARN DecisionTree Classifier with Monte Carlo Cross Validation The IRIS flower is a popular example in the field of machine learning. It is a type of flower that has different variations, such as the setosa, virginica, and versicolor. In this blog, we will be discussing how to classify the IRIS …
IRIS Flower Classification using SKLEARN DecisionTree Classifier with Grid Search Cross Validation The IRIS flower is a popular example in the field of machine learning. It is a type of flower that has different variations, such as the setosa, virginica, and versicolor. In this blog, we will be discussing how to classify the …
End-to-End Machine Learning: Boston House Price Prediction in R Boston House Price Prediction is a machine learning task that involves predicting the median value of owner-occupied homes in Boston, Massachusetts, based on certain characteristics such as the number of rooms, the crime rate, and the distance to employment centers. Understanding the value of houses can …
End-to-End Machine Learning: Abalone Prediction in R Abalone prediction is a machine learning task that involves identifying the age of an abalone, which is a type of sea snail, based on certain characteristics such as the abalone’s length, diameter, height, and weight. Understanding the age of the abalone can be useful for both the commercial …
End-to-End Machine Learning: IRIS Flower Prediction in R IRIS flower prediction is a machine learning task that involves identifying the type of IRIS flower based on certain characteristics such as the flower’s petal length and width, and sepal length and width. There are three types of IRIS flowers: Setosa, Versicolor, and Virginica, and being able …
End-to-End Machine Learning: Glass Type Prediction in R Glass type prediction is a machine learning task that involves identifying the type of glass based on certain characteristics such as the glass’s refractive index, sodium content, and magnesium content. Different types of glass have different properties and uses, for example, tempered glass is used for car …