मुख्य सामग्री पर जाएँ

Introduction to Experiment Tracking

This webinar shows you how to get started with experiment tracking, a pivotal yet frequently overlooked aspect of the data science lifecycle.
Jinen Setpal
Jinen Setpal

अपना निःशुल्क खाता बनाएँ

अभ्यास और ट्रैक अपनी प्रगति को।

Google के साथ जारी रखेंजारी रखकर, आप हमारी उपयोग की शर्तें, हमारी गोपनीयता नीति को स्वीकार करते हैं और यह भी कि आपका डेटा USA में संग्रहीत है।

It is very common for organizations to run many experiments - such as A/B tests - at the same time. The knowledge gained from these tests can only be acted upon if they are carefully managed and studied. This webinar shows you how to get started with experiment tracking, a pivotal yet frequently overlooked aspect of the data science lifecycle. You'll learn about the importance experiment tracking plays in ensuring reproducibility and how using it can allow you to update your internal understanding of your task more systematically. You'll also discover how to use DagsHub to manage a single data experiment, then how to scale this to many experiments.

Key Takeaways:

  • Learn the steps involved in tracking data experiments.
  • Learn how to scale your use of experiments.
  • Learn how to use DagsHub for managing experiments and other machine learning projects.
Additional Resources
 
We use DagsHub in this webinar, sign up for an account here.
 

विषय

Data ScienceData AnalysisData Scientist

संबंधित

ट्यूटोरियल

Python Exploratory Data Analysis Tutorial

कोड-अलॉंग

Running Machine Learning Experiments in Python

और देखें →