Sahar Seidi Khorramabadi's repositories
machine-learning-engineering-for-production-public
Public repo for DeepLearning.AI MLEP Specialization
awesome-tensorflow
TensorFlow - A curated list of dedicated resources http://tensorflow.org
ml-system-design-pattern
System design patterns for machine learning
mlops-zoomcamp
Free MLOps course from DataTalks.Club
lightweight_mmm
LightweightMMM 🦇 is a lightweight Bayesian Marketing Mix Modeling (MMM) library that allows users to easily train MMMs and obtain channel attribution information.
machine-learning-coursera-1
This repo is specially created for all the work done my me as a part of Coursera's Machine Learning Course.
machine-learning-systems-design
A booklet on machine learning systems design with exercises. NOT the repo for the book "Designing Machine Learning Systems"
mlflow-deployments
Source code for the post Effortless deployments with MLFlow, showcasing how logging models using MLFLow can provide you want to easily deploy them in production later.
ProgrammingAssignment2
Repository for Programming Assignment 2 for R Programming on Coursera
python-object-oriented-programming-4413110
This is a repository for the LinkedIn Learning course Python Object-Oriented Programming
quadprogIP
quaprogIP solver for Non-Convex quadratic programs
RepData_PeerAssessment1
Peer Assessment 1 for Reproducible Research
SGDLibrary
MATLAB/Octave library for stochastic optimization algorithms: Version 1.0.17
stanford-cs229
🤖 Exercise answers to the problem sets from the 2017 machine learning course cs229 by Andrew Ng at Stanford
Supply-Chain-Analytics
Project based on business intelligence and visualisation for supply chain domain using Power BI and supply chain KPIs
system-design-primer
Learn how to design large-scale systems. Prep for the system design interview. Includes Anki flashcards.
tensorflow
An Open Source Machine Learning Framework for Everyone
tensorflow_cookbook
Code for Tensorflow Machine Learning Cookbook
Wine-Rating-Predictor-ML-Model
Automated ML pipeline with Python, Docker, Luigi, SciKit-Learn and Pandas to predict wine quality ratings