Gayathri Selvaganapathiaienthusiast.hashnode.dev·Aug 30, 2024Predicting Customer Churn Using XGBoost: A Comprehensive GuideTable of Contents Introduction Understanding the Dataset Setting Up the Environment Clone the GitHub Repository Install Dependencies Load the Dataset Run the Jupyter Notebook 4. Data Preprocessing Handling Missing Data and Categorical Var...DiscussCustomer Experience
Gayathri Selvaganapathiaienthusiast.hashnode.dev·Aug 29, 2024Predicting Energy Consumption Using Time Series ForecastingTable of Contents Introduction Understanding Time Series Data Project Overview Data Preparation Loading and Inspecting the Data Visualizing the Data 5. Feature Engineering Extracting Time-Based Features Implementing Feature Engineering ...DiscussTime Series Forecasting
Sai Aneeshlhcee3.hashnode.dev·Aug 15, 2024PerceptronsThe perceptron, a foundational concept in artificial intelligence, was introduced by Frank Rosenblatt in the 1950s. It's a simplified model of a biological neuron, designed to mimic the human brain's ability to learn and make decisions. A perceptron ...DiscussPerceptron
Niladri Dasniladridas.hashnode.dev·Aug 11, 2024Everything You Need to Know About XGBoostXGBoost (eXtreme Gradient Boosting) is a popular open-source machine learning library that provides a scalable and efficient way to perform gradient boosting. It works on Linux, Microsoft Windows, and macOS. It's widely used for classification and re...DiscussInterpretable
Md Shahriyar Al Mustakim Mitulmitul-shahriyar.hashnode.dev·Aug 8, 2024Machine Learning : Model Selection Techniques, XGBoost (Part 34)Till now, we have been dividing our main dataset to Training Set and Test set Let's now split the Training set to 10 parts Then what we're going to do is we're going to train the data on nine of these folds and keep one fold as an unseen fold for v...DiscussML Model selection
Sujit Nirmal blackshadow.hashnode.dev·Jul 18, 2024How Gradient Boosting Machines Work: A Machine Learning OverviewIntroduction Gradient Boosting Machines (GBM) are a powerful ensemble learning technique that builds models sequentially, with each new model correcting the errors of the previous ones. This method is highly effective for both classification and regr...Discuss#Finetuning Models
Sanika Nandpuresanikanandpure.hashnode.dev·May 19, 2024decision tree boosting and xgboostBoosting is a way of making decision tree ensembles both more efficient as well as more accurate. It derives from a practice that you may be already familiar with known as deliberate practice. When preparing for a test, it is often a smart practice t...DiscussXgboost
Juan Carlos Olamendyjuancolamendy.hashnode.dev·Apr 16, 2024Ensemble Learning: Combining Models for Improved PerformanceIntroduction In the field of machine learning, ensemble learning has emerged as a powerful technique to improve the performance and robustness of predictive models. Ensemble learning involves combining multiple models to make more accurate and reliab...DiscussMachine Learning
K Ahameddatailm.hashnode.dev·Jan 11, 2024Harmonizing Predictive Power: Unleashing the Magic of Ensemble MethodsMachine learning has revolutionized the way we approach complex problems, offering unprecedented insights and solutions across various domains. One key challenge in the field is to build models that not only generalize well but also exhibit robustnes...DiscussMachine Learningensemble methods
Juan Carlos Olamendyjuancolamendy.hashnode.dev·Dec 12, 2023Unveiling the Power Trio of Machine Learning: Bagging, Boosting, and StackingImagine you're on a quest for the Holy Grail of predictions in the vast and intricate world of data. What if I told you that the secret weapon isn't a singular magical model, but a team of models working in harmony? Welcome to the realm of ensemble l...DiscussMachine Learning
