R Data Science Project
Learn practical R data science skills through hands-on tutorials covering exploratory analysis, machine learning, data visualization, and building interactive web applications with Shiny.
Python Data Science Project
Learn Python for data science through hands-on projects covering machine learning, web scraping, exploratory data analysis, and computational drug discovery. Gain practical skills using popular libraries and tools.
Weka Data Mining Tutorials
Learn data mining with Weka's user-friendly interface. Master regression, classification, and drug discovery models through hands-on tutorials and practical examples.
Train and Evaluate Classification Models
Train and evaluate classification models using Scikit-Learn. Learn binary classification, logistic functions, thresholds, and performance metrics for effective machine learning categorization.
Tensorflow Tutorial for Beginner in Python - Hindi
हिंदी में TensorFlow की शुरुआत से लेकर उन्नत अवधारणाओं तक का व्यापक प्रशिक्षण, जिसमें न्यूरल नेटवर्क, रिग्रेशन, वर्गीकरण और CNN शामिल हैं।
Precision, Recall, Confusion Matrix and F1-Score - Machine Learning Tutorials in Hindi
Aprenda a evaluar modelos de aprendizaje automático utilizando métricas clave como precisión, recall, matriz de confusión y puntuación F1, con ejemplos prácticos en Python.
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.
Full Data Science Mock Interview Featuring Kylie Ying
Comprehensive mock data science interview covering bot detection on social media, featuring behavioral questions, feature selection, model implementation, dataset creation, and technical details.
Get Started With Tidymodels Using Vaccination Rate Data
Explore MMR vaccination rates using tidymodels in R, from data preparation to Bayesian modeling and result comparison.
Introduction to Text Analytics with R - Overview
Explore text analytics with R: tokenization, feature engineering, classification models. Learn data cleaning, analysis, and visualization using a spam dataset. Practical introduction for aspiring data scientists.
Feature Engineering and Modeling Techniques for Menu Design at HelloFresh
Discover how HelloFresh uses data-driven approaches to optimize menu design, predict recipe performance, and align product offerings with customer preferences and business strategies.
Enhancing Older Adults' Safe Use of Automated Vehicles Using Eye-Tracking Data
Explore a framework for detecting mode confusion in older drivers using automated vehicles, utilizing eye-tracking data and machine learning to enhance safety and usability.
Build a ML Classification Model in 12 Lines with PyCaret
Learn to rapidly build and evaluate a heart disease prediction model using PyCaret, a low-code ML library. Covers data loading, model training, testing, and saving in just 12 lines of code.
Machine Learning in R - Repurpose Machine Learning Code for New Data
Learn to adapt machine learning code in R for new datasets. Explore data understanding, visualization, and model building techniques using the DHFR dataset as an example.
ML Production Pipelines: Building and Deploying a Classification Model
Learn to build and deploy production-ready machine learning pipelines using Python, Databricks, and MLflow. Explore training and prediction workflows, model registration, and deployment options for both batch and on-demand processing.
Developing a Match-Making Algorithm Between Customers and Go-Jek Products
Explore how GoJek developed a personalized recommendation system using PySpark to match customers with relevant products and vouchers, improving conversion rates.
Feature Estimation for Punching Tool Wear at the Edge
Discover how to monitor punching tool wear through acceleration measurement and edge processing, comparing TSFEL and MiniRocket algorithms for real-time classification of tool conditions in metal manufacturing.
Delivering Delivery Time Prediction - Machine Learning Lessons and Model Optimization
Discover practical insights into ML model development, from handling unclear requirements to ensemble classification techniques and determining optimal probability cutoffs for delivery predictions.
Tackling Advanced Classification Using Snorkel Flow
Explore advanced classification techniques using Snorkel Flow, addressing challenges in label schema, high cardinality, and multi-label problems while leveraging foundation models for production-ready solutions.
An Agile Approach to Threat Modeling for Securing Open Source Projects - EdgeX Foundry Case Study
Learn an agile approach to threat modeling for open source projects using EdgeX Foundry as an example. Discover practical steps, STRIDE model application, and strategies to evaluate security risks effectively.
Unveiling Hidden Backdoors in Manifold Distribution Gaps
Explore backdoor attacks in deep neural networks, focusing on manifold distribution gaps. Learn to generate stealthy triggered samples and extend decision boundaries for enhanced security understanding.