Probability Libraries

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Probability Libraries

Machine Learning Foundations: Linear Algebra, Calculus, Statistics & Computer Science

There are eight subjects in the curriculum, organized into four subject areas. See the "Machine Learning House" section below for detail on why these are the essential foundational subject areas: Lat…

Data Science Roadmap from A to Z

Pandas

General statistics, mathematical programming, and numerical/scientific computing scripts and notebooks in Python

Jupyter Notebooks on the topics of statistical analysis, mathematics, and numerical/sceintific computing (in Python).

Jupyter Notebooks for Springer book "Python for Probability, Statistics, and Machine Learning"

The motive behind Creating this repo is to feel the fear of mathematics and do what ever you want to do in Machine Learning , Deep Learning and other fields of AI

The motive behind Creating this repo is to feel the fear of mathematics and do what ever you want to do in Machine Learning , Deep Learning and other fields of AI . I am going to upload new material…

Python-for-Probability-Statistics-and-Machine-Learning-2E

Second edition of Springer Book Python for Probability, Statistics, and Machine Learning

This book, fully updated for Python version 3.6+, covers the key ideas that link probability, statistics, and machine learning illustrated using Python modules in these areas. All the figures and nu…

$discrete-math-python-scripts$

Python code snippets from Discrete Mathematics for Computer Science specialization at Coursera

Why are some arguments convincing while others are not? What makes an argument convincing? How can you establish your argument in such a way that no room for doubt is left? How can mathematical think…

UQpy (Uncertainty Quantification with python) is a general purpose Python toolbox for modeling uncertainty in physical and mathematical systems.

To engage in conversations about uncertainty quantification, or ask question about UQpy usage and functionality refer to the UQpy's discussions tab: UQpy (Uncertainty Quantification with python) is a…

Mathematical & Statistical topics to perform statistical analysis and tests; Linear Regression, Probability Theory, Monte Carlo Simulation, Statistical Sampling, Bootstrapping, Dimensionality reduction techniques (PCA, FA, CCA), Imputation techniques, Statistical Tests (Kolmogorov Smirnov), Robust Estimators (FastMCD) and more in Python and R.

Required Files: Linear regression is a linear approach to model the relationship between a scalar response (dependent varaible) and one or more explanatory variables (independent variables). The case…

Introduction to statistics featuring Python. This series of lecture notes aim to walk you through all basic concepts of statistics, such as descriptive statistics, parameter estimations, hypothesis testing, ANOVA and etc. All codes are straightforward to understand.

[Last updated on 19th Aug 2022] This is a series of lecture notes that I prepared in my statistics tutorial (used prepared for one-night new-hire statistical training in hedge fund), which are suppos…

🇦🇮 Deep Learning AI course on Coursera (Andrew Ng)

“So, ask yourself: If what you're working on succeeds beyond your wildest dreams, would you have significantly helped other people? If not, then keep searching for something else to work on. Otherwis…

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