Скачать клипы PyData Tel Aviv Meetup: Maintainable complex Algorithmic Code in Production ↓

PyData Tel Aviv Meetup: Maintainable complex Algorithmic Code in Production - Uri Yanover

PyData Tel Aviv Meetup: Maintainable complex Algorithmic Code in Production - Uri Yanover

PyData Tel Aviv Meetup: Continuous Delivery in Python on a Massive Scale - Or Been-Zeev

PyData Tel Aviv Meetup: Continuous Delivery in Python on a Massive Scale - Or Been-Zeev

PyData Tel Aviv Meetup: Monitoring Machine Learning at Scale - Naama Horesh and Anna Reznikov

PyData Tel Aviv Meetup: Monitoring Machine Learning at Scale - Naama Horesh and Anna Reznikov

PyData Tel Aviv Meetup: Working full-time on Open Source Software - Matti Pincus

PyData Tel Aviv Meetup: Working full-time on Open Source Software - Matti Pincus

PyData Tel Aviv Meetup: Deep Analysis of Clickstream - Segev Arbiv

PyData Tel Aviv Meetup: Deep Analysis of Clickstream - Segev Arbiv

PyData Tel Aviv Meetup: Data Science MGMT Panel

PyData Tel Aviv Meetup: Data Science MGMT Panel

PyData Chicago: Running Notebooks in Production? Blessing or Curse? by Eduardo Blancas

PyData Chicago: Running Notebooks in Production? Blessing or Curse? by Eduardo Blancas

PyData Tel Aviv Meetup: Lightning Talks 1 - Part 2

PyData Tel Aviv Meetup: Lightning Talks 1 - Part 2

Machine Learning Models in Production

Machine Learning Models in Production

Pydata Berlin Meetup February 2021: The Foundation of our Machine Learning Platform at GetYourGuide

Pydata Berlin Meetup February 2021: The Foundation of our Machine Learning Platform at GetYourGuide

Ori Cohen: Using DBT and Python to Build Production Pipelines in Snowflake (HE)|PyData Tel Aviv 2025

Ori Cohen: Using DBT and Python to Build Production Pipelines in Snowflake (HE)|PyData Tel Aviv 2025

Dean Pleban - ML in Production–What does “Production” even mean? | PyData Global 2022

Dean Pleban - ML in Production–What does “Production” even mean? | PyData Global 2022

Dr. Paul Elvers: Getting Started with MLOps: Best Practices for Production-Ready ML Systems | PyData

Dr. Paul Elvers: Getting Started with MLOps: Best Practices for Production-Ready ML Systems | PyData

Piero Ferrante: Should I develop my own DS library? Maybe. | PyData New York City 2019

Piero Ferrante: Should I develop my own DS library? Maybe. | PyData New York City 2019

Elle O'Brien - DevOps for Science: using continuous integration | PyData Global 2020

Elle O'Brien - DevOps for Science: using continuous integration | PyData Global 2020

Mike Müller: Aspect-oriented Programming - Diving deep into Decorators

Mike Müller: Aspect-oriented Programming - Diving deep into Decorators

Imaad Mohamed Khan Production Ready Machine Learning Pipelines using ZenML PyCon 2023

Imaad Mohamed Khan Production Ready Machine Learning Pipelines using ZenML PyCon 2023

Ep393: Luis Voloch | Co-Founder, Chief Technology Officer, Immunai

Ep393: Luis Voloch | Co-Founder, Chief Technology Officer, Immunai

Mike Müller: Aspect-oriented Programming - Diving deep into Decorators

Mike Müller: Aspect-oriented Programming - Diving deep into Decorators

Justin J. Nguyen: Exposing Dark Data in the enterprise with custom NLP | PyData Miami 2019

Justin J. Nguyen: Exposing Dark Data in the enterprise with custom NLP | PyData Miami 2019

Скачать клипы PyData Tel Aviv Meetup: Maintainable complex Algorithmic Code in Production бесплатно и без регистрации