Noza's repositories
feature-selection-for-machine-learning
Code Repository for the online course Feature Selection for Machine Learning
feature-engineering-for-machine-learning
Code Repository for the online course Feature Engineering for Machine Learning
powerbi-jupyter
A Custom Jupyter Widget Library for Power BI
TaxiFareWebsite
Prediction app for taxi
ml_hacks
Приёмы в машинном обучении
noza_ml_project
The package desribes the ML project that I undertook at Le Wagon Data Science Bootcamp
dotfiles
Default configuration for Le Wagon's students
zero-to-mastery-ml
All course materials for the Zero to Mastery Machine Learning and Data Science course.
causallift
CausalLift: Python package for causality-based Uplift Modeling in real-world business
Hands-On-Gradient-Boosting-with-XGBoost-and-Scikit-learn
Hands-On Gradient Boosting with XGBoost and Scikit-learn Published by Packt
Pricing-optimization-Model
Optimize revenues through pricing algorithm in python - Demand with uniform distribution
DataAnalyst-NanoDegree
Data Science Portfolio - DAND - Udacity - Projects -Data Analytics
Programming-for-Data-Science-with-Python-Udacity-Nanodegree
This repository contains projects did for Udacity Programming For Data Science With Python Nanodegree.
pycaret-demo-tfmeetup
Introducing PyCaret 1.0 in TF Meetup
Customer-Analytics-in-Python
I use various Data Science and machine learning techniques to analyze customer data using STP framework. I preprocessed the data, performed segmentation, hierarchical clustering, k-means, PCA techniques with a lot of visualizations to segment and understand customer data. I have performed Purchase Analytics (both descriptive analysis and predictive analysis). Used deep learning to enhance my model.
fundamentals
Fundamentals of data exploration, data manipulation, data cleaning, and data analysis
flask_api
Creating a Machine Learning API using Flask - Repository for AV Article
Hands-On-Data-Science-for-Marketing-1
Hands-On Data Science for Marketing, published by Packt
machine_learning_examples
A collection of machine learning examples and tutorials.