100-pandas-puzzles

100 data puzzles for pandas, ranging from short and simple to super tricky (60% complete)

albumentation-library

amazing-feature-engineering

Feature engineering is the process of using domain knowledge to extract features from raw data via data mining techniques. These features can be used to improve the performance of machine learning algorithms. Feature engineering can be considered as applied machine learning itself.

apply-probability-distributions-in-dataset

in this Jupyter notebook we explain probability distributions and apply them in real datasets

arithmetic-operators

audi-car-analysis

Audi car data analysis

awsim

bank-customer-churn-

Bank Customer Churn using Ensemble learning

binary-search-algorithm

binarysearchtree

Binary Search Tree Module

books-recommendation-system-collaborative-filter-

Books Recommendation System (Collaborative Filter)

cameras

classification-sheeps

connect-database-python

Connect sqlite to python for using some queries by Pandas

content-based-recommendation-system-phones-rs-

Content Based Recommendation System (Phones RS)

data-augmentation

Using Albumentation for Data Augmentation

data-science-interview-questions-answers

data-science-roadmap

Data Science Roadmap from A to Z

data_structure

Data_Structure by cpp

datacamp

This repository contains assignments on courses related to data science from Data camp

datasetcars-machine-learning-

demographic-recommendation-system-books-rs-

Demographic Recommendation System (Books RS)

divsion

ercot-electricity-prediction

Focus on Feature Engineering

feature-engineering-for-machine-learning

Code repository for the online course Feature Engineering for Machine Learning

find-ruuner_up-score

find_a_string

finding-the-percentage

good-guys

gradcam-deep-learning