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Data Science

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  • Feature Engineering
  • Feature Selection
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  • Interpretability
  • Machine Learning
  • Predictive Models
Predictive Model Deployment
January 25, 2021 Joseph Sibony AI Education

A Brief Introduction to Predictive Model Deployment

You’ve built your model, you’ve located your data sources, and you’ve done all the initial processing and ETL to get your data how you want it.

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What is Feature Enginering
January 4, 2021 Joseph Sibony Data Science

What is Feature Engineering?

Your data is teeming with potential insights, ready to be teased out by predictive models. But doing that isn’t only about knowing what questions to ask

data science predictions
December 16, 2020 Joseph Sibony AI Education

Looking Back and Predicting 2021: Q&A With Shai Yanovski

2020’s been a crazy year, but even with (or, should we say, because of) all the insanity, data science has had a whirlwind 12 months. The

Data Preparation Using Python
November 30, 2020 Explorium Data Science Team Data Science

How to Approach Data Preparation Using Python

As they say, the proof is in the pudding, and data preparation is where the pudding is put together. Any mistakes you make here will be

ML deployment
November 9, 2020 Joseph Sibony Data Science

ML Initiatives Aren’t Doomed To Fail — If You Build Them Right

Not to sound alarmist or anything, but machine learning (ML) initiatives can be risky. It’s true, they sound amazing, and you hear success stories left and

data pipeline
October 28, 2020 Joseph Sibony Data Science

How Explorium Upgrades Your Data Pipeline

Let’s say you own a factory that makes computers. You need to have a steady pipeline of parts and raw materials. You can approach this necessity

data for machine learning
October 21, 2020 Joseph Sibony Data Enrichment

Without Data, There’s No ML — Why You Should Focus on Data First

Like Italian cooking, data science is all about quality ingredients. It’s not enough to simply have a lot of data; you need to make sure the

data preparation tools
October 7, 2020 Explorium Data Science Team Data Science

4 Ways To Know If You’re Using the Right Data Preparation Tools

There’s nothing more frustrating than laboring away at the early stages of your data science project, only to discover that the success of your model is

Better insights from automatic feature engineering
September 8, 2020 Joseph Sibony Data Science

How Explorium’s Automated Feature Engineering Improves Your Data Science

So, you’ve built a dataset you’re happy with, and your machine learning (ML) model ready to start making predictions left and right. Easy as pie, right?

Categories
  • All posts
  • AI Education
  • Automation
  • Business Intelligence
  • Data Acquisition
  • Data Enrichment
  • Data Science
  • Explainability
  • Feature Engineering
  • Feature Selection
  • General
  • Interpretability
  • Machine Learning
  • Predictive Models
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