List: ML-new-and-useful | Curated by Julio Cárdenas-Rodríguez | Medium

Julio Cárdenas-Rodríguez

Feb 19, 2024

17 stories

ML-new-and-useful

In

TDS Archive

by

Jacky Kaub

The Biggest Weakness Of Boosting Trees

Why distribution drifts can really hurt your models

Feb 12, 2024

The Biggest Weakness Of Boosting Trees

Feb 12, 2024

Düzgün İlaslan

How to serve Machine Learning model using FastAPI+MLFlow+MINIO+MySQL

This is the easy way to serve ML models with FastAPI

Jun 4, 2023

How to serve Machine Learning model using FastAPI+MLFlow+MINIO+MySQL

Jun 4, 2023

Rayyan Shaikh

Mastering BERT: A Comprehensive Guide from Beginner to Advanced in Natural Language Processing…

Introduction: A Guide to Unlocking BERT: From Beginner to Expert

Aug 26, 2023

Google Bert

Aug 26, 2023

In

Towards AI

by

Bex T.

Forget PIP, Conda, requirements.txt! Use Poetry Instead And Thank Me Later

Pain-free dependency management is finally here

Jun 24, 2023

Forget PIP, Conda, requirements.txt! Use Poetry Instead And Thank Me Later

Jun 24, 2023

In

Becoming Human: Artificial Intelligence Magazine

by

Lak Lakshmanan

No, You Don’t Need MLOps

Keep It Simple: the complexity of full MLOps is rarely needed

Sep 18, 2022

No, You Don’t Need MLOps

Sep 18, 2022

In

Snowflake Builders Blog: Data Engineers, App Developers, AI/ML, & Data Science

by

Phani Raj

Migrating from PySpark to Snowpark Python Series — Part 1

Dated: June 2022

Jun 9, 2022

Migrating from PySpark to Snowpark Python Series — Part 1

Jun 9, 2022

In

Becoming Human: Artificial Intelligence Magazine

by

Kovendhan Venugopal

Mathematical Introduction to GloVe Word Embedding

Topics covered in this article are:

May 8, 2021

Mathematical Introduction to GloVe Word Embedding

May 8, 2021

In

TDS Archive

by

Edwin Tan

How to Prepare Scikit-Learn Models for Production

Serve scikit-learn models with FastAPI and Docker

Sep 27, 2022

How to Prepare Scikit-Learn Models for Production

Sep 27, 2022

In

TDS Archive

by

Vinay Kudari

SQLAlchemy — Python Tutorial

We often encounter data as Relational Databases. To work with them we generally would need to write raw SQL queries, pass them to the…

Aug 23, 2018

SQLAlchemy — Python Tutorial

Aug 23, 2018

Liam Roberts

Stop Pickling your ML Models. Use ONNX instead!

So the first thing I will say is that there is nothing inherently wrong with pickling your models. It’s just that it imposes several…

Aug 31, 2022

Stop Pickling your ML Models. Use ONNX instead!

Aug 31, 2022

This story is no longer available

In

The Prefect Blog

by

Khuyen Tran

Orchestrate Your Data Science Project with Prefect 2.0

Make Your Data Science Pipeline Resilient Against Failures

Jun 29, 2022

Orchestrate Your Data Science Project with Prefect 2.0

Jun 29, 2022

This story is no longer available

In

Data For Science

by

Bruno Gonçalves

Causal Inference — Part XV — Mediation

This is the fifteenth post on the series we work our way through “Causal Inference In Statistics” a nice Primer co-authored by Judea Pearl…

Feb 14, 2021

Causal Inference — Part XV — Mediation

Feb 14, 2021

In

TDS Archive

by

Kurtis Pykes

Normalized Discounted Cumulative Gain

A Metric for Evaluating Recommendation Engines

Aug 8, 2020

Normalized Discounted Cumulative Gain

Aug 8, 2020

Tamara Alexandra Cucumides

Learning-to-rank with LightGBM (Code example in python)

LightGBM: brief description and usage

Jan 22, 2020

Learning-to-rank with LightGBM (Code example in python)

Jan 22, 2020

In

Towards AI

by

Michał Oleszak

Estimating Model Performance without Ground Truth

It’s possible, as long as you keep your probabilities calibrated

May 12, 2022

Estimating Model Performance without Ground Truth

May 12, 2022

Julio Cárdenas-Rodríguez
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Scientist, modeling geek, immigrant, father, writer-at-heart, scientifically religious, and many other contradictions.
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