Bayesian Inversion of an Acoustic-Gravity Model for Predictive Tsunami Simulation
Explore Bayesian inversion of acoustic-gravity models for predictive tsunami simulation, focusing on real-time monitoring and early-alert systems using near-field data observation.
Leveraging Neighborhood Socioeconomic Data to Predict Individual Experiences - A Healthcare Application
Explore how neighborhood socioeconomic data can predict individual healthcare experiences through machine learning, examining predictive accuracy and demographic variations in social risk assessment.
Data Science Solutions with Cortana Analytics
Comprehensive tutorial on building predictive models using Microsoft Azure Machine Learning, covering data processing, model creation, deployment, and practical applications in various domains.
Propensity Model for Marketing Campaign in eCommerce Industry
Learn to develop propensity models for targeted marketing campaigns in e-commerce using machine learning algorithms. Discover key drivers of customer data to predict subscription probability and improve conversion rates.
Kaggle Competition Starter Notebook Walkthrough
Learn to create a starter notebook for a Kaggle competition, covering feature engineering, cross-validation, and LightGBM modeling. Gain practical insights from a Kaggle Grandmaster on predictive modeling and Python coding.
TMCF Workshop Use-Cases - Counterfactual CPMS & Emerging COVID Work, Niels Peek
Exploring causal inference in AI prediction algorithms for decision-making, focusing on 'what if' scenarios in healthcare and insurance, with applications to COVID-19 pandemic response.
Time Series Forecasting with PyCaret
Explore automated time series forecasting with PyCaret's low-code module. Learn setup, EDA, training, and forecasting techniques to streamline your predictive modeling workflow.
Use Tidymodels Workflowsets to Predict Human-Computer Interactions from Star Trek
Explore machine learning with tidymodels workflowsets to predict speaker type in Star Trek interactions, featuring data preprocessing, model evaluation, and result analysis.
Predict Housing Prices in Austin TX with Tidymodels and XGBoost
Explore feature engineering for boosted tree models using Austin housing data. Learn to incorporate text information as indicator variables and tune models for accurate price predictions.
Class Imbalance and Classification Metrics With Aircraft Wildlife Strikes
Explore how handling class imbalance affects classification metrics using aircraft wildlife strike data, with focus on sensitivity and specificity in predictive modeling.
Partial Dependence Plots for Mario Kart World Records
Explore decision tree modeling and partial dependence profiles for Mario Kart world records using tidymodels and DALEX, with a focus on predicting shortcut usage.
Impute Missing Data and Handle Class Imbalance for Himalayan Climbing Expeditions
Learn to predict survival in Himalayan climbing expeditions using tidymodels in R. Explore data handling, imputation, and modeling techniques for imbalanced datasets.
How to Handle High Cardinality Predictors for Data on Museums in the UK
Explore effect and likelihood encodings for high cardinality predictors in tidymodels, using UK museum data to demonstrate practical applications.
Deploy Different Prediction Types for a Bigfoot Sighting Model
Learn to deploy various prediction endpoints for a Bigfoot sighting model using vetiver, including feature engineering, logistic regression, and natural language processing techniques.
Cuneyt Akçora - TDA on Networks – Applications and Scalability Issues
Explore Topological Data Analysis on networks, focusing on applications in blockchain for ransomware detection, price prediction, and anomaly detection. Learn about persistent homology and TDAMapper algorithms.
Constraining Ωm with Phase-Space Information of Galaxies - Natali Soler Matubaro De Santi
Explore innovative techniques for constraining the matter density parameter using galaxy phase-space data, combining astrostatistics and machine learning to advance our understanding of cosmic structure formation.
PyScript Tutorial: Machine Learning with Scikit-Learn - Training and Interactive Prediction
Create interactive machine learning app with PyScript: upload CSV, train models, and make predictions using Pandas, Panel, and Scikit-Learn.
Kaggle Competition Submission - Learn Python ML in 30 Days - Day 11
Learn to participate in machine learning competitions on Kaggle. Create and submit predictions, improving your skills through hands-on practice in a real-world competitive environment.
Building Your First Machine Learning Model and Model Validation - Day 9
Learn to build and validate your first machine learning model using scikit-learn. Explore techniques for handling large datasets, selecting features, and evaluating model performance through hands-on exercises.
AutoML Frameworks Accuracy Comparison with Kaggle Data
Explore the performance of popular AutoML frameworks across 10 Kaggle competitions, analyzing their accuracy and effectiveness in tackling real-world machine learning challenges.
Data Science Against COVID-19 - Nuria Oliver, PhD
Explore how data science combats COVID-19 through mobility models, epidemiological predictions, and large-scale surveys. Learn key technical skills and insights from Dr. Nuria Oliver's multidisciplinary team of volunteer scientists.