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Portfolio
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Portfolio
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Portfolio
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Portfolio
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Details about this repository
+
Project Description
- Welcome to my Python Programming repository, your gateway to mastering one of the most versatile and widely-used programming languages.
- This collection of Jupyter notebooks and tutorials is thoughtfully structured to take you on a journey from Python basics to more advanced
- topics, making your learning experience both enriching and enjoyable.
+ This machine learning project is aimed at (briefly describe the project's objective or purpose).
+ It utilizes various machine learning techniques, such as (mention specific algorithms or methods used).
+ This machine learning project covers various topics, including:
+
+ - - Basics about machine learning
+ - - Machine learning fundamentals and various algorithms
+ - 1. Machine learning fundamentals and various algorithms
+ - 2. List of regression models
+ - 3. Linear regression models
+ - 4. Basics of statistics, Descriptive statistics, Inferential statistics, Overfitting-underfitting.
+ - - Few example projects (time series data analysis)
+ - - Statistics-fundamental
+
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+
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- Project URL: https://github.com/arunsinp/Python-programming
+ Project URL: https://arunsinp.github.io/MonteCarlo-simulation/
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Portfoio Details
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Portfoio Details
Details about this repository
- Welcome to my Python Programming repository, your gateway to mastering one of the most versatile and widely-used programming languages.
- This collection of Jupyter notebooks and tutorials is thoughtfully structured to take you on a journey from Python basics to more advanced
- topics, making your learning experience both enriching and enjoyable.
+ Monte Carlo simulation is named after the famous Monte Carlo Casino in Monaco, which is known for its games of chance. It is a
+ computational technique that uses random sampling and statistical analysis to model and solve problems. By repeatedly sampling from
+ probability distributions, Monte Carlo simulation allows us to estimate the behavior of complex systems or processes.
+
Monte Carlo simulations and Machine learning algorithms
+
+ - Monte Carlo simulations are a class of computational techniques that use random sampling to approximate and analyze complex systems or problems.
+ - While Monte Carlo simulations themselves are not typically considered machine learning algorithms, they can be combined with machine learning techniques to enhance their capabilities.
+ - It's important to note that the specific choice of machine learning algorithms in Monte Carlo simulations depends on the nature of the problem, the available data, and the objectives of the simulation.
+ - Different algorithms may be more suitable for different scenarios, and their selection should be based on careful analysis and experimentation.
+
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+
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-
+
-
+