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Problem-solving tools offered by digital technology

Data Science Dojo

Tech-Vidvan ’s “Top 10”: Linear Regression Logistic Regression Decision Trees Naive Bayes K-Nearest Neighbors Support Vector Machine K-Means Clustering Principal Component Analysis Neural Networks Random Forests P.

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Unlocking data science 101: The essential elements of statistics, Python, models, and more

Data Science Dojo

It provides a fast and efficient way to manipulate data arrays. Pandas is a library for data analysis. It provides a high-level interface for working with data frames. Matplotlib is a library for plotting data. Decision trees are used to classify data into different categories.

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Elevating business decisions from gut feelings to data-driven excellence

Dataconomy

In this era of information overload, utilizing the power of data and technology has become paramount to drive effective decision-making. Decision intelligence is an innovative approach that blends the realms of data analysis, artificial intelligence, and human judgment to empower businesses with actionable insights.

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2024 Tech breakdown: Understanding Data Science vs ML vs AI

Pickl AI

Key Components In Data Science, key components include data cleaning, Exploratory Data Analysis, and model building using statistical techniques. ML focuses on algorithms like decision trees, neural networks, and support vector machines for pattern recognition. billion by 2029.

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Top 10 Data Science Interviews Questions and Expert Answers

Pickl AI

Machine Learning Algorithms Candidates should demonstrate proficiency in a variety of Machine Learning algorithms, including linear regression, logistic regression, decision trees, random forests, support vector machines, and neural networks. Here is a brief description of the same.

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Predicting Heart Failure Survival with Machine Learning Models — Part II

Towards AI

That post was dedicated to an exploratory data analysis while this post is geared towards building prediction models. Feel free to try other algorithms such as Random Forests, Decision Trees, Neural Networks, etc., Motivation The motivating question is— ‘What are the chances of survival of a heart failure patient?’.

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A very machine way of network management

Dataconomy

How could machine learning be used in network traffic analysis? Machine learning is fundamentally changing the landscape of network traffic analysis by automating the process of data analysis and interpretation.