Remove Cross Validation Remove Data Mining Remove Data Quality
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Machine Learning Models: 4 Ways to Test them in Production

Data Science Dojo

TensorFlow There are three main types of TensorFlow frameworks for testing: TensorFlow Extended (TFX): This is designed for production pipeline testing, offering tools for data validation, model analysis, and deployment. TensorFlow Data Validation: Useful for testing data quality in ML pipelines.

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Artificial Intelligence Using Python: A Comprehensive Guide

Pickl AI

Pandas: A powerful library for data manipulation and analysis, offering data structures and operations for manipulating numerical tables and time series data. Scikit-learn: A simple and efficient tool for data mining and data analysis, particularly for building and evaluating machine learning models.

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Basic Data Science Terms Every Data Analyst Should Know

Pickl AI

Summary : This article equips Data Analysts with a solid foundation of key Data Science terms, from A to Z. Introduction In the rapidly evolving field of Data Science, understanding key terminology is crucial for Data Analysts to communicate effectively, collaborate effectively, and drive data-driven projects.

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The Age of Health Informatics: Part 1

Heartbeat

Image from "Big Data Analytics Methods" by Peter Ghavami Here are some critical contributions of data scientists and machine learning engineers in health informatics: Data Analysis and Visualization: Data scientists and machine learning engineers are skilled in analyzing large, complex healthcare datasets.