Kendrick Onyango's Projects
A repository for 100 days of Code Challenge
📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.
Apache Arrow is a cross-language development platform for in-memory data. It specifies a standardized language-independent columnar memory format for flat and hierarchical data, organized for efficient analytic operations on modern hardware. It also provides computational libraries and zero-copy streaming messaging and interprocess communication. Languages currently supported include C, C++, Java, JavaScript, Python, and Ruby.
Visualize equations using Latex notation inside ChatGPT
Example application code for the python architecture book
A machine learning tool for automated prediction engineering. It allows you to easily structure prediction problems and generate labels for supervised learning.
The country converter (coco) - a Python package for converting country names between different classification schemes.
See ReadMe for details!
Analyzing the Craigslist Vehicle dataset is a comprehensive task, and the depth of your analysis can vary depending on your specific goals. Below, I'll provide an overview of steps you can take to analyze this dataset: Data Exploration and Preparation:
Analysis of Credit Card Default Dataset of Taiwan for Machine Learning
Free Data Engineering course!
For extensive instructor led learning
Data Science boot camp aims to make the field of data science accessible and understandable to a wide range of individuals, regardless of their background or expertise.
A repository listing out the potential sources which will help you in preparing for a Data Science/Machine Learning interview. New resources added frequently.
Some materials for those in data science
Collection of data science projects in Python
Just for Git & GitHub Practs
The open-source repo for docs.github.com
dplyr: A grammar of data manipulation
Apache ECharts is a powerful, interactive charting and data visualization library for browser
Fast Lane to Learning R!
:books: Freely available programming books
Learnings on Git & Github
Git Exercise
The Open Source Data Science Masters
This is a package is a powerful package that lets you make better formatted tables for visuals. it also lets you make better labels and colors to make it easier for you and others to see tables. It starts with tibbles and lets you transform it to gt tables. This package can be used in a lot of ways. this is because a lot of fields need tables. Whether this be for stocks, medical, or the statistical field. A lot of people need to be able to see and comprehend tables and this package lets you make them more accessible. One of the most used functions is pretty simple and it is the gt() function. This function is simple and it transforms the tibble into a gt table. It is demonstrated below.
This is a package is a powerful package that lets you make better formatted tables for visuals. it also lets you make better labels and colors to make it easier for you and others to see tables. It starts with tibbles and lets you transform it to gt tables. This package can be used in a lot of ways. this is because a lot of fields need tables. Whether this be for stocks, medical, or the statistical field. A lot of people need to be able to see and comprehend tables and this package lets you make them more accessible. One of the most used functions is pretty simple and it is the gt() function. This function is simple and it transforms the tibble into a gt table. It is demonstrated below.