Alternatives and similar repositories for Machine-Learning-for-Imbalanced-Data

Users that are interested in Machine-Learning-for-Imbalanced-Data are comparing it to the libraries listed below

• PacktPublishing / Applied-Machine-Learning-Explainability-Techniques
  Applied Machine Learning Explainability Techniques, published by Packt
  ☆246Updated 3 weeks ago
• PacktPublishing / Practical-Deep-Learning-at-Scale-with-MLFlow
  Practical Deep Learning at Scale with MLFlow, published by Packt
  ☆162Updated 3 weeks ago
• BexTuychiev / tricking-data-science
  A book of subtle code tricks and gem resources for all things data, machine learning and deep learning.
  ☆169Updated last year
• deshwalmahesh / DataScience-StudyMaterial
  Just some stuff for Interview questions, books, annotated paper, notes, cheat sheets etc etc related to ML,AI, Deep Learning and Data Sc…
  ☆119Updated 3 months ago
• khuyentran1401 / cicd-mlops-demo
  Demo for CI/CD in a machine learning project
  ☆115Updated 2 years ago
• Paulescu / build-and-deploy-real-time-feature-pipeline
  Develop and deploy a real-time feature pipeline in Python, using Bytewax 🐝 and Hopsworks Feature Store.
  ☆134Updated 2 years ago
• solegalli / DataTalks.Club2022
  ☆20Updated 3 years ago
• vinija / AI-Coding
  AI algorithms
  ☆141Updated last year
• ThinamXx / MLOps
  The repository contains a list of projects which I will work on while learning and implementing MLOps.
  ☆79Updated 2 years ago
• ThinamXx / ML..Interview..Preparation
  Preparation for Machine Learning Interview
  ☆186Updated last year
• trojrobert / MLOps_roadmap_and_curriculum
  Curriculum and roadmap from 0 to Mastery for MLOps. Adding value to your machine learning model by deploying it for people to use it to s…
  ☆184Updated 3 years ago
• Lightning-AI / dl-fundamentals
  Deep Learning Fundamentals -- Code material and exercises
  ☆397Updated last year
• manuelgilm / mlflow_for_ml_dev
  Repository with code examples of mlflow
  ☆227Updated 3 months ago
• vinija / LeetCode
  ☆215Updated last year
• Paulescu / bytewax-hopsworks-example
  Compute and store real-time features for crypto trading using Bytwax (stream processing) and Hopsworks (Feature Store)
  ☆145Updated 2 years ago
• deshwalmahesh / ML-Models-from-Scratch
  Repo for ML Models built from scratch such as Self-Attention, Linear +Logistic Regression, PCA, LDA. CNN, LSTM, Neural Networks using Nu…
  ☆50Updated 10 months ago
• PacktPublishing / Developing-Kaggle-Notebooks
  ☆143Updated 3 weeks ago
• kennethleungty / MLOps-Specialization-Notes
  Notes for Machine Learning Engineering for Production (MLOps) Specialization course by DeepLearning.AI & Andrew Ng
  ☆378Updated 2 years ago
• hamzafarooq / advanced-llms-course
  Code files for advanced LLM Course
  ☆215Updated last year
• prsdm / mlops-project
  ☆156Updated last year
• evidentlyai / ml_observability_course
  Free Open-source ML observability course for data scientists and ML engineers. Learn how to monitor and debug your ML models in productio…
  ☆98Updated last year
• PacktPublishing / Machine-Learning-Engineering-with-Python
  Machine Learning Engineering with Python
  ☆185Updated 3 weeks ago
• youssefHosni / My-Medium-Articles-Friendly-Links
  Friendly link to all of my medium articles
  ☆179Updated last year
• init27 / Deep-Learning-Book-Supplementary-Materials
  Supplementary Materials for the Deep Learning Book by Ian Goodfellow et al
  ☆53Updated 2 years ago
• brianrisk / Stock-Prediction-Neural-Network-and-Machine-Learning-Examples
  Examples of python neural net and ML stock prediction methods with sample stock data.
  ☆271Updated last year
• ashishpatel26 / LLM-Engineering-Crash-Course
  LLM Engineering CrashCourse
  ☆103Updated last year
• 5x12 / course-prodml
  ☆60Updated last year
• PacktPublishing / Machine-Learning-Engineering-with-Python-Second-Edition
  ☆254Updated 3 weeks ago
• PacktPublishing / EngineeringMLOps
  Engineering MLOps, published by Packt
  ☆190Updated 3 weeks ago
• youssefHosni / Getting-Started-with-Generative-AI
  A curated list of articles and tutorials to start with and understand generative AI
  ☆309Updated last year