An AI Engineer's Guide to Machine Learning with Keras
Comprehensive guide to building and evaluating machine learning models using Keras, covering data preparation, model creation, training, and performance analysis with practical examples.
Build Your Machine Learning Pipeline in These 4 Simple Steps - Loan Prediction Scikit-Learn Example
Aprenda a construir um pipeline completo de machine learning usando scikit-learn para previsão de empréstimos, desde a ingestão de dados até o uso do modelo salvo para previsões.
Access 2019 Beginner Tutorial
Comprehensive tutorial on Microsoft Access 2019 for beginners, covering database creation, table design, data import, relationships, queries, forms, and reports. Includes hands-on exercises and advanced topics.
Hierarchical Clustering on Asymmetric Networks
Explore hierarchical clustering techniques for asymmetric networks, examining methodologies and applications in data analysis and network science.
Dimension Reduction - An Overview
Comprehensive overview of dimension reduction techniques, from linear methods like PCA to nonlinear approaches such as LLE, Isomap, t-SNE, and UMAP, with practical application to chemical reaction data.
Skeletonization Algorithms With Theoretical Guarantees for Point Clouds
Explore skeletonization algorithms for point clouds, including Mapper, alpha-Reeb graphs, and Homologically Persistent Skeleton. Compare their performance on synthetic and real data sets.
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.
Variational Methods for Computational Microscopy - IPAM at UCLA
Explore variational methods for computational microscopy with Stanley Osher, covering advanced techniques and applications in image processing and analysis.
ExaFEL - Achieving Real-Time XFEL Data Analysis Using Exascale Hardware
Explore real-time data analysis for X-ray Free Electron Laser experiments using high-performance computing, focusing on challenges, workflow design, and performance insights for future scientific applications.
Non-Astrophysical Transients in LIGO Detectors: Help With Machine Learning
Explore machine learning techniques for diagnosing non-astrophysical transients in LIGO detectors, enhancing gravitational wave detection and analysis in multi-messenger astrophysics.
Embedding as a Tool for Algorithm Design
Explore embedding algorithms for structured data prediction, combinatorial optimization, and dynamic network processes. Learn innovative approaches to algorithm design using latent variable models and mean field techniques.
The Missing Signal
Explore representation learning and its applications in AI research with insights from Facebook's leading expert.
An Introduction to Hamiltonian Monte Carlo Method for Sampling
Explore the Hamiltonian Monte Carlo method for efficient sampling in high-dimensional spaces, its theoretical foundations, and practical applications in optimization and machine learning.
Machine Learning Tutorial for Beginners
Comprehensive TensorFlow tutorial covering data handling, neural networks, and model building. Learn to clean, analyze, and process data for machine learning applications.
Dual Principal Component Pursuit
Explore a novel approach to learning subspaces from corrupted data, tolerating high outlier ratios and dimensions. Discover algorithms and theoretical guarantees for this non-convex optimization problem.
The Missing Link- How AI Can Help Create a Safer Society and Better Businesses
Explore how AI and NLP can enhance crime-solving, improve business efficiency, and create safer societies by automating information linking and reducing investigative time.
Production Machine Learning Monitoring- Principles, Patterns and Techniques
Practical deep dive on production monitoring of machine learning models, covering standard techniques and advanced paradigms like concept drift, outlier detection, and explainability, with hands-on examples and architectural patterns.
Latency SLOs Done Right - Calculating and Setting Accurate Service Level Objectives
Explore accurate latency SLO calculation methods, including histogram-based approaches, to set mathematically correct quantiles and improve service level objectives for better monitoring and performance management.
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.
Scalable AutoML for Time Series Forecasting Using Ray
Explore scalable AutoML for time series forecasting using Ray, covering feature generation, model selection, and hyper-parameter tuning. Learn from real-world applications and experiences in various industries.