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Creating a Simple Z-test Calculator using Streamlit

Analytics Vidhya

It is a significant step in the process of decision making, powered by Machine Learning or Deep Learning algorithms. One of the popular statistical processes is Hypothesis Testing having vast usability, not […]. The post Creating a Simple Z-test Calculator using Streamlit appeared first on Analytics Vidhya.

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What is the P-Value? Hypothesis Testing and its Ties to Machine Learning

ODSC - Open Data Science

Hypothesis Testing and Machine Learning Now here’s the kicker: when you do machine learning (including that simple linear regression above), you are in fact searching for hypotheses that identify relationships in the data. Some data points only have a 0.0005976% chance to have arranged themselves randomly around a line.

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Introduction to applied data science 101: Key concepts and methodologies 

Data Science Dojo

It directly focuses on implementing scientific methods and algorithms to solve real-world business problems and is a key player in transforming raw data into significant and actionable business insights. Statistical analysis and hypothesis testing Statistical methods provide powerful tools for understanding data.

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Mathematics for Artificial Intelligence: Everything You Must Know

Pickl AI

Introduction Mathematics forms the backbone of Artificial Intelligence , driving its algorithms and enabling systems to learn and adapt. Key Takeaways Mathematics is crucial for optimising AI algorithms and models. Mastering these areas is critical for AI professionals to design scalable and efficient AI solutions.

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Revolutionizing physics: How AI is transforming research and discovery

Dataconomy

AI, particularly machine learning algorithms, can predict outcomes based on vast amounts of data, significantly speeding up the modeling process. AI algorithms, especially those based on neural networks, are adept at handling such tasks.

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

Data Science Dojo

The ability to understand the principles of probability, hypothesis testing, and confidence intervals enables data scientists to validate their findings and ascertain the reliability of their analyses. It provides a wide range of mathematical functions and algorithms. SciPy is a library for scientific computing.

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Cracking the Code: An Introduction to Mathematics for Machine Learning

Pickl AI

These tools enable data analysis, model building, and algorithm optimization, forming the backbone of ML applications. Feed data into an algorithm, and out comes predictions, classifications, or insights that seem almost intuitive. Think of ML algorithms as sophisticated tools.