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Data mining hacks 101: Listing down best techniques for beginners

Data Science Dojo

Data mining has become increasingly crucial in today’s digital age, as the amount of data generated continues to skyrocket. In fact, it’s estimated that by 2025, the world will generate 463 exabytes of data every day, which is equivalent to 212,765,957 DVDs per day!

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5 Ways Data Analytics Helps Investors Maximize Stock Market Returns

Smart Data Collective

Ramneet Rekhi of New York University and his colleagues from Stanford discussed this in their paper titled Finding Undervalued Stocks with Machine Learning. The authors concluded that nonlinear support vector machines can help investors choose investments with the best future returns. Optimize Your Investments.

Analytics 142
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Unleashing the Power of Applied Text Mining in Python: Revolutionize Your Data Analysis

Pickl AI

Machine Learning algorithms, including Naive Bayes, Support Vector Machines (SVM), and deep learning models, are commonly used for text classification. Text Mining Tools and Libraries Various tools and libraries have been developed to facilitate text-mining tasks. Can text mining handle multiple languages?

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Elevating business decisions from gut feelings to data-driven excellence

Dataconomy

At its core, decision intelligence involves collecting and integrating relevant data from various sources, such as databases, text documents, and APIs. This data is then analyzed using statistical methods, machine learning algorithms, and data mining techniques to uncover meaningful patterns and relationships.

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Eager Learning and Lazy Learning in Machine Learning: A Comprehensive Comparison

Pickl AI

Support Vector Machines (SVM) : SVM is a powerful Eager Learning algorithm used for both classification and regression tasks. It constructs a hyperplane to separate different classes during training and uses it to make predictions on new data. What Are The Examples of Eager Learning Algorithms?

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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.

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

IBM Journey to AI blog

One of the best ways to take advantage of social media data is to implement text-mining programs that streamline the process. What is text mining? Text analysis takes it a step farther by focusing on pattern identification across large datasets, producing more quantitative results.