Machine learning for beginner(Data Science enthusiast)
-
Updated
Sep 7, 2023 - Jupyter Notebook
Machine learning for beginner(Data Science enthusiast)
Implement a momentum trading strategy in Python and test to see if it has the potential to be profitable
PyImpetus is a Markov Blanket based feature subset selection algorithm that considers features both separately and together as a group in order to provide not just the best set of features but also the best combination of features
This is an initiative to help understand Statistical methods and Machine learning in a naive manner. You will find scripts, and theoretical contents required to clarify concepts, especially for bio-informatic students.
This repository is created for storing the components of Statistical Tests of One Pop, Two Pops and Three or more pops using Python.
R package for computing multiple hypothesis tests on rows/columns of a matrix or a data.frame
Test the phenomenon of Stroop Effect
OCS (BP): Examine global patterns of obesity across rural and urban regions
Calculate independent samples t test using summary statistics
Supervised classification to predict rock facies and a T-test flow to evaluate the prediction performance.
Data driven fault detection in chemical processes: Application to Tennessee Eastman Plant
Statistical analysis of vehicle production metrics with R
An analysis of titanic dataset from Kaggle using Python pandas and mathplotlib. Includes the definition of questions to be answered, detailed description of the exploratory steps, and communication of conclusions.
High School SSVEP-BCI Research Project to improve classification accuracy of captured EEG signals
Marketing Campaigns A/B Testing on Jupyter Notebook
Scrapped reviews of 500 Restaurants from yelp and Tripadvisor each. And tried to analyze the difference in ratings.
I will include two ways of t tests that compare conversion rate and click through rate of two groups
Retrieving, Processing, and Visualizing Data with Python
about statistical techniques for Data Science
Add a description, image, and links to the t-test topic page so that developers can more easily learn about it.
To associate your repository with the t-test topic, visit your repo's landing page and select "manage topics."