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Master the top 7 statistical techniques for better data analysis

Data Science Dojo

Get ahead in data analysis with our summary of the top 7 must-know statistical techniques. Top statistical techniques – Data Science Dojo Counterfactual causal inference: Counterfactual causal inference is a statistical technique that is used to evaluate the causal significance of historical events.

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Top 8 Machine Learning Algorithms

Data Science Dojo

Common Classification Algorithms: Logistic Regression: A popular choice for binary classification, it uses a mathematical function to model the probability of a data point belonging to a particular class. Decision Trees: These work by asking a series of yes/no questions based on data features to classify data points.

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Exploring the dynamic fusion of AI and the IoT

Dataconomy

Here are some ways AI enhances IoT devices: Advanced data analysis AI algorithms can process and analyze vast volumes of IoT-generated data. By leveraging techniques like machine learning and deep learning, IoT devices can identify trends, anomalies, and patterns within the data.

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Data-driven Attribution Modeling

Data Science Blog

First, a robust data platform (such as a customer data platform; CDP) that can integrate data from various sources, such as tracking systems, ERP systems, e-commerce platforms to effectively perform data analytics. In contrast, multi-touch attribution leverages individual user-level data from various channels.

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Deciding What Algorithm to Use for Earth Observation.

Towards AI

Tailoring the algorithm to the specific data type and application enhances performance and interpretability, facilitating clear communication and informed decision-making. – Supervised Classification: Requires labeled training data. – Algorithms: Support Vector Machines (SVM), Random Forest, Neural Networks.

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8 of the Top Python Libraries You Should be Using in 2024

ODSC - Open Data Science

Without this library, data analysis wouldn’t be the same without pandas, which reign supreme with its powerful data structures and manipulation tools. Pandas provides a fast and efficient way to work with tabular data. It is widely used in data science, finance, and other fields where data analysis is essential.

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

IBM Journey to AI blog

As organizations collect larger data sets with potential insights into business activity, detecting anomalous data, or outliers in these data sets, is essential in discovering inefficiencies, rare events, the root cause of issues, or opportunities for operational improvements.