Remove Cross Validation Remove Data Mining Remove Deep Learning
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Artificial Intelligence Using Python: A Comprehensive Guide

Pickl AI

Summary: This guide explores Artificial Intelligence Using Python, from essential libraries like NumPy and Pandas to advanced techniques in machine learning and deep learning. 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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List of Python Libraries for Data Science

Pickl AI

Scikit-Learn Scikit Learn is associated with NumPy and SciPy and is one of the best libraries helpful for working with complex data. Its modified feature includes the cross-validation that allowing it to use more than one metric.

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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.

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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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[Updated] 100+ Top Data Science Interview Questions

Mlearning.ai

Once the data is acquired, it is maintained by performing data cleaning, data warehousing, data staging, and data architecture. Data processing does the task of exploring the data, mining it, and analyzing it which can be finally used to generate the summary of the insights extracted from the data.

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How to Choose MLOps Tools: In-Depth Guide for 2024

DagsHub

Moving the machine learning models to production is tough, especially the larger deep learning models as it involves a lot of processes starting from data ingestion to deployment and monitoring. It provides different features for building as well as deploying various deep learning-based solutions.

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Ever Wondered How Similar patterns are identified?

Mlearning.ai

To address such tasks and uncover behavioral patterns, we turn to a powerful technique in Machine Learning called Clustering. Originally used in Data Mining, clustering can also serve as a crucial preprocessing step in various Machine Learning algorithms. How would we tackle this challenge? K = 3 ; 3 Clusters.