Remove Data Visualization Remove Deep Learning Remove Support Vector Machines
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8 of the Top Python Libraries You Should be Using in 2024

ODSC - Open Data Science

Matplotlib The main benefit of Matplotlib is its stunning visualizations. Programmers most frequently utilize Matplotlib for data visualization projects. The data visualization market could reach approximately $7.76 It’s a plotting library with a vibrant community of around 700 contributors. Not a bad list right?

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Five machine learning types to know

IBM Journey to AI blog

Classification algorithms —predict categorical output variables (e.g., “junk” or “not junk”) by labeling pieces of input data. Classification algorithms include logistic regression, k-nearest neighbors and support vector machines (SVMs), among others.

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Data science vs. machine learning: What’s the difference?

IBM Journey to AI blog

The fields have evolved such that to work as a data analyst who views, manages and accesses data, you need to know Structured Query Language (SQL) as well as math, statistics, data visualization (to present the results to stakeholders) and data mining. Machine learning and deep learning are both subsets of AI.

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A very machine way of network management

Dataconomy

It constructs multiple decision trees and combines their predictions to achieve accurate results in identifying different types of network traffic Support Vector Machines (SVM) : SVM is used for both classification and anomaly detection.

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Anomaly detection in machine learning: Finding outliers for optimization of business functions

IBM Journey to AI blog

The main difference being that while KNN makes assumptions based on data points that are closest together, LOF uses the points that are furthest apart to draw its conclusions. Unsupervised learning Unsupervised learning techniques do not require labeled data and can handle more complex data sets.

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What Does the Modern Data Scientist Look Like? Insights from 30,000 Job Descriptions

ODSC - Open Data Science

Machine Learning As machine learning is one of the most notable disciplines under data science, most employers are looking to build a team to work on ML fundamentals like algorithms, automation, and so on. Deep Learning Deep learning is a cornerstone of modern AI, and its applications are expanding rapidly.

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Leveraging user-generated social media content with text-mining examples

IBM Journey to AI blog

Machine learning algorithms like Naïve Bayes and support vector machines (SVM), and deep learning models like convolutional neural networks (CNN) are frequently used for text classification. And with advanced software like IBM Watson Assistant , social media data is more powerful than ever.