Why Communication is the Best Skill You Can Develop as a Programmer
Desarrolla habilidades de comunicación esenciales para programadores. Mejora la comprensión de requisitos, revisiones de código y colaboración en equipo.
DBT and Python - How to Write Reusable and Testable Pipelines
Develop reusable and testable data pipelines using DBT and Python. Learn best practices for version control, DAGs, and unit testing in SQL and Python-based models.
One Analysis a Day Keeps Anomalies Away - Detecting and Analyzing Data Anomalies
Explore Python techniques for data observability, anomaly detection, and root cause analysis in multivariate time series. Learn to distinguish anomalies from data drift and turn insights into opportunities.
Verifiable Data Science via Interactive Proofs
Explore interactive proofs for verifiable data science, enhancing trust and reliability in scientific computations and analyses.
The Imposter Staff Engineer's Journey to Leadership
Explore a staff engineer's journey through imposter syndrome, leadership challenges, and unexpected triumphs while leading a team to create innovative solutions.
Building a MovieLens Recommender System
Explore recommendation systems and build your own using collaborative and content-based filtering techniques in Python with MovieLens dataset.
Why ML in Production is Still Broken
Explore challenges in deploying ML projects to production, focusing on the disconnect between development and real-world application. Learn key aspects distinguishing ML from traditional software engineering.
How to Monitor Machine Learning Stacks - Detecting and Addressing Special Issues
Discover advanced monitoring techniques for ML stacks, addressing unique challenges beyond traditional metrics to ensure robust performance and early issue detection.
Machine Learning with PyCaret - Workshop
Explore rapid prototyping and ML pipeline development using PyCaret, an open-source, low-code machine learning library for Python.
Team Roles in a Machine Learning Project and Project Flow
Develop context for data science projects, understand team roles, and build a data-driven culture. Learn about machine learning techniques and their appropriate applications.
Knowledge Graph Recommendation Systems for COVID-19
Explore knowledge graph recommendation systems for COVID-19, leveraging Python skills to enhance understanding of pandemic-related data and insights.
Managing Data Science in the Enterprise
Learn effective strategies for managing data science teams, processes, and technologies in enterprise settings, avoiding pitfalls and implementing best practices for breakthrough results.
Turbo-Charging Data Science with AutoML
Explore open-source AutoML tools and cloud provider options to enhance data science workflows. Hands-on demonstration of installation, usage, and unique features for improved efficiency.
Computer Vision in Practice - Building an End-to-End Pipeline for Object Detection and Segmentation
Build an end-to-end image segmentation pipeline using deep learning. Learn dataset customization, model training, validation, testing, and mobile deployment techniques.
Holistic Health Metrics for ML-Based Products
Explore holistic health metrics for ML-based products. Learn where and when to collect data, model, post-model, and business-level metrics to ensure system accuracy and reliability.
Build, Train, and Deploy Models with Amazon SageMaker
Learn to build, train, and deploy machine learning models using Amazon SageMaker through hands-on experience. Gain practical skills in ML model development and implementation on AWS platform.
Women in AI - Transitioning Careers, Challenges, and Opportunities
Explore career transitions, challenges, and opportunities for women in AI through insights from industry experts and leaders.
Validate and Monitor Your AI and Machine Learning Models
Discover techniques for validating and monitoring advanced AI and ML models, ensuring long-term performance and business adoption in various industries.
Simplify ML Pipeline Automation and Tracking Using Kubeflow and Serverless Functions
Simplify ML pipeline automation and tracking with Kubeflow and serverless functions. Learn to streamline your machine learning workflows for improved efficiency and productivity.
Introduction to Machine Learning with Python
Explore machine learning fundamentals using Python, covering key concepts and practical applications in this hands-on workshop led by a field engineer from Domino.
ML Monitoring ML: Scalable Monitoring of ML Models in Production Environments
Explore scalable ML model monitoring in production. Learn key performance measures, anomaly detection techniques, and an open-source agent for automated tracking and alerting of model issues.