exploratory-data-analysis

Always know what to expect from your data.

1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.

Compilation of R and Python programming codes on the Data Professor YouTube channel.

Cleanlab's open-source library is the standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.

Build 12 Data Apps in Python with Streamlit

Business intelligence as code: build fast, interactive data visualizations in SQL and markdown

Automatically visualize your pandas dataframe via a single print! 📊 💡

Visualize and compare datasets, target values and associations, with one line of code.

Beautiful visualizations of how language differs among document types.

Complete-Life-Cycle-of-a-Data-Science-Project

Ways of doing Data Science Engineering and Machine Learning in R and Python

Open-source low code data preparation library in python. Collect, clean and visualization your data in python with a few lines of code.

this repository features assignments and projects from the iNeuron full stack data science course, providing valuable resources for learners to enhance their skills and apply their knowledge.

Collection of must read papers for Data Science, or Machine Learning / Deep Learning Engineer

Classification of Breast Cancer diagnosis Using Support Vector Machines

🌝 Lottery prediction besides of following "law of proability","Probability: Independent Events", there are still "Saying "a Tail is due", or "just one more go, my luck is due to change" is called The Gambler's Fallacy" existed.

A day to day plan for this challenge. Covers both theoritical and practical aspects

A machine learning approach to classify songs by mood.

Desbordante is a high-performance data profiler that is capable of discovering many different patterns in data using various algorithms. It also allows to run data cleaning scenarios using these algorithms. Desbordante has a console version and an easy-to-use web application.

Kernel Density Estimation in Python