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Data Science to Predict the Next Hit Song
November 6, 2019 Maël Fabien Data Science

Using Data Science to Predict the Next Hit Song (Part 1)

It comes as no surprise that the music industry is tough. When you decide to produce an artist or invest in a marketing campaign for a

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evaluation metrics
October 23, 2019 Eilon Baer Predictive Models

Top 10 Evaluation Metrics for Classification Models

It's important to understand that none of the following evaluation metrics for classification are an absolute measure of your machine learning model’s accuracy. However, when measured

filter and wrapper methods
August 11, 2019 Aviv Nutovitz Data Science

Demystifying Feature Selection: Filter vs Wrapper Methods

Feature selection algorithms are increasingly growing in significance. In this article, we will cover (and compare) two popular feature selection methodologies - Filter and Wrapper.

shap partial dependence plot
July 24, 2019 Maël Fabien Data Science

Interpretability and explainability (Part 2)

The whole idea behind interpretable and explainable ML is to avoid the black box effect.

data science blog
July 15, 2019 Maël Fabien Data Science

Interpretability and explainability (Part 1)

The whole idea behind interpretable and explainable ML is to avoid the black box effect.

machine learning model deployment
July 11, 2019 Maor Shlomo Data Science

The ultimate machine learning model deployment checklist

While there is some room for error while integrating models into production environments, there is also a very good probability that these issues will eventually lead to disaster. And that’s exactly why we have created this pre-model deployment checklist.

machine learning algorithms
July 9, 2019 Maël Fabien Data Enrichment

Who's the painter?

Better features, better data

feature discovery
June 23, 2019 Omer Har Data Science

The spectrum of complexity

Demystifying the old battle between transparent, explainable models and more accurate, complex models.

data science blog
June 22, 2019 Eilon Baer Feature Engineering

How feature selection could actually harm your machine learning models when used incorrectly

(or – “how I f***ed up my text classifier while thinking it’s performing well")

Categories
  • All posts
  • AI Education
  • AI for FinTech
  • AI in the news
  • Automation
  • B2B Marketing
  • Business Intelligence
  • Consumer Goods
  • Data Acquisition
  • Data Architecture
  • Data Enhancement
  • Data Enrichment
  • Data Quality
  • Data Science
  • Digital Marketing
  • Explainability
  • External Data
  • External Data for eCommerce
  • External Data Orchestration
  • Feature Engineering
  • Feature Selection
  • General
  • Interpretability
  • Machine Learning
  • Predictive Models
  • Security & Privacy
  • Tutorials
  • unknown unknowns
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