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data-science-interviews

Data science interview questions and answers

deep-learning-drizzle

Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!

deep-learning-in-production

In this repository, I will share some useful notes and references about deploying deep learning-based models in production.

deep-learning-time-series

List of papers, code and experiments using deep learning for time series forecasting

deploying-machine-learning-models

Code for the online course "Deployment of Machine Learning Models"

dynamicmnl

Greedy-Like Algorithms for Dynamic Assortment Optimization Under Multinomial Logit Preferences

effective_pandas_book

Errata and code for Effective Pandas book

efficient-python-for-data-scientists

fpp3-python-readalong

Python-centered read-along of Forecasting: Principles and Practice

github-actions-for-ci

github-slideshow

A robot powered training repository :robot:

handson-ml3

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

m4-methods

Data, Benchmarks, and methods submitted to the M4 forecasting competition

machine-learning-interview-enlightener

This repo is meant to serve as a guide for Machine Learning/AI technical interviews.

markdown-portfolio

ml-for-beginners

12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all

mlbookcamp-code

The code from the Machine Learning Bookcamp book and a free course based on the book

mlcoursecamp

mlops-zoomcamp

Free MLOps course from DataTalks.Club

optimization-demo-files

Examples on numerical optimization

python-deepdive

Python Deep Dive Course - Accompanying Materials

python-fundamentals

Course materials for my Udemy Python Fundamentals course

sam

selenium-repo

stroustrup-ppp

Chapter work from Bjarne Stroustrup's Programming Principles and Practice text

tanya-data-viz

Personal data visualization side projects.

time-series-forecasting-with-python

A use-case focused tutorial for time series forecasting with python

weeklyforecasting

This repository contains the experiments related with a new baseline model that can be used in forecasting weekly time series. This model uses the forecasts of 4 sub-models: TBATS, Theta, Dynamic Harmonic Regression ARIMA and a global Recurrent Neural Network (RNN), and optimally combine them using lasso regression.