Modeling Dwarf Galaxy Formation with UniverseMachine - Richie Wang (Stanford)
Explore dwarf galaxy formation using UniverseMachine, a statistical tool for modeling galaxy evolution in cosmological simulations. Learn about abundance matching, multiresolution simulations, and future research directions.
Predict Astronauts' Mission Duration With Tidymodels and Bootstrap Aggregation
Explore astronaut mission duration prediction using R's tidymodels and bootstrap aggregation, featuring data analysis, preprocessing, and model evaluation techniques.
Python for AI: Exploring and Cleaning Data with Pandas
Learn to explore, clean, and prepare data for machine learning using Pandas. Covers handling missing values, outliers, categorical data, and feature preparation for model training.
Azure Synapse Analytics: Building End-to-End Analytics Solutions
Unified analytics service integrating data warehousing, big data, and BI. Query data flexibly using serverless or dedicated resources at scale. Ingest, explore, prepare, manage, and serve data for immediate insights.
Feature Exploration, Visualization, and Predictive Modeling with R and Azure ML
Explore predictive analytics using the Titanic dataset. Learn feature exploration and visualization with R, then build models using Azure ML Studio for efficient experimentation.
Detecting Eye Disease Using Deep Learning - Kaggle Top 1% Solution, No Ensemble
Learn to detect eye disease using deep learning, with a top-ranked Kaggle solution. Covers data preprocessing, loss functions, augmentation, and resolution techniques for improved accuracy in medical image analysis.
Build Your First Model with PyTorch and Python - PyTorch Tutorial for Beginners
Learn to implement a Simple Linear Regression model using PyTorch, covering data exploration, model creation, tensor conversion, training, and prediction analysis in this beginner-friendly tutorial.
Getting Started with PyTorch Lightning for Deep Learning
Explore PyTorch Lightning for easier Deep Learning projects, using Google's GoEmotions dataset to build an emotion classification model with practical coding examples.
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.
Probabilistic Deep Learning in TensorFlow - The Why and How - ODSC Europe 2019
Explore probabilistic deep learning in TensorFlow, focusing on Bayesian techniques, uncertainty modeling, and practical applications using TensorFlow Probability for more robust and interpretable neural networks.
Build Features for Machine Learning from Netflix Description Text
Learn to build machine learning features from Netflix description text and train a support vector machine model using tidymodels, exploring data analysis, feature engineering, and model evaluation techniques.
Build a Predictive Text Model for Avatar: The Last Airbender with Tidymodels
Predict Avatar: The Last Airbender speakers using text features and tidymodels in R. Learn model-agnostic variable importance and handle class imbalance in this data analysis tutorial.
Price Optimisation - From Exploration to Productionising - David Adey, PhD & Alexey Drozdetskiy, PhD
Explore dynamic price optimization using machine learning, from data analysis to cloud deployment. Learn about feature encoding, model selection, efficiency improvements, and practical implementation strategies for revenue growth.
Data Management - Full Stack Deep Learning - Spring 2021
Explore ML infrastructure for data management: ingestion, storage, processing, exploration, labeling, and versioning. Learn about tools and best practices for effective dataset handling in deep learning projects.
Introducing MLflow for End-to-End Machine Learning on Databricks
Learn to predict life expectancy using health data with MLflow. Covers data engineering, exploration, model tuning, and deployment on Databricks' unified analytics platform powered by Apache Spark.
Introducing MLflow for End-to-End Machine Learning on Databricks
Explore end-to-end machine learning with MLflow on Databricks: from data engineering to model deployment, using health data to predict life expectancy through Spark, hyperopt, and interactive dashboards.
Dominating the DBIR Data
Explore data analysis techniques for cybersecurity incidents, covering data collection, processing, and validation. Learn to generate meaningful statistics and uncover novel findings in security datasets.
Identifying Hidden Dependencies
Discover how Honeycomb improved system reliability through intentional node termination, uncovering bugs and progressing towards continuous experimentation for enhanced resilience and scalability.
How Prometheus Revolutionized Monitoring at SoundCloud
Explore how Prometheus transformed SoundCloud's monitoring, addressing challenges in microservices architecture and offering insights into its implementation, features, and impact on system observability.
How to Make Sure Your Data Science Isn't Vulnerable to Attack
Learn to protect your data science projects from vulnerabilities through exploration, preparation, algorithm application, and effective communication of insights and risks.
Data, Design, Code
Explore the process of creating web-based data visualizations, from topic selection and data preparation to designing visual encodings, with insights on using D3.js for custom, impactful visualizations.