Alternatives and similar repositories for deep_learning_for_structured_data:

Users that are interested in deep_learning_for_structured_data are comparing it to the libraries listed below

• PacktPublishing / Machine-Learning-Engineering-with-MLflow
  Machine Learning Engineering with MLflow, published by Packt
  ☆115Updated 9 months ago
• amueller / aml
  Applied Machine Learning with Python
  ☆78Updated last year
• BenWilson2 / ML-Engineering
  Reference code base for ML Engineering, Manning Publications
  ☆128Updated 3 years ago
• PacktPublishing / Mastering-Machine-Learning-Algorithms-Second-Edition
  Mastering Machine Learning Algorithms Second Edition, published by Packt
  ☆61Updated 4 years ago
• PacktPublishing / Deep-Learning-with-fastai-Cookbook
  Deep Learning with fastai Cookbook, published by Packt
  ☆59Updated 3 years ago
• PacktPublishing / Machine-Learning-Using-TensorFlow-Cookbook
  Machine Learning Using TensorFlow Cookbook, published by Packt
  ☆68Updated 2 years ago
• canyon289 / PyTestforDataScience_PyDataLA
  Pytest for Data Science Beginners
  ☆58Updated 6 years ago
• MaartenGr / feature-engineering
  Tips for Advanced Feature Engineering
  ☆52Updated 4 years ago
• datamllab / automl-in-action-notebooks
  Jupyter notebooks for the code samples of the book "Automated Machine Learning in Action"
  ☆93Updated 2 years ago
• PacktWorkshops / The-Unsupervised-Learning-Workshop
  An Interactive Approach to Understanding Unsupervised Learning Algorithms
  ☆28Updated 4 years ago
• PacktPublishing / Practical-Machine-Learning-with-TensorFlow-2.0-and-Scikit-Learn
  Practical Machine Learning with TensorFlow 2.0 and Scikit-Learn [Video], published by Packt
  ☆56Updated 2 years ago
• KishManani / PyDataLondon2022
  Slides for "Feature engineering for time series forecasting" talk
  ☆59Updated 2 years ago
• alexander-n-thomas / spark-nlp-book
  ☆60Updated 4 years ago
• pycaret / pycaret-demo-mlflow
  pycaret-demo-mlflow
  ☆30Updated 3 years ago
• FrancescaLazzeri / AutoML-for-Timeseries-Forecasting-Berlin-MeetUp
  ☆34Updated 3 years ago
• dennisbakhuis / Tutorials
  Jupyter Notebooks and other material from tutorial sessions on Machine Learning, Data Science, and related
  ☆56Updated 3 years ago
• PacktWorkshops / The-Deep-Learning-with-PyTorch-Workshop
  ☆33Updated last year
• Apress / applied-data-science-using-pyspark
  Source Code for 'Applied Data Science Using PySpark' by Ramcharan Kakarla, Sundar Krishnan, and Sridhar Alla
  ☆46Updated 3 years ago
• AlexIoannides / notes-and-demos
  Study notes and demos.
  ☆12Updated last year
• PacktPublishing / Cleaning-Data-for-Effective-Data-Science
  Cleaning Data for Effective Data Science, published by Packt
  ☆97Updated 2 years ago
• trangel / stats-with-python
  Learning statistics with Python
  ☆53Updated 4 years ago
• outerbounds / dsbook
  Code samples for the Effective Data Science Infrastructure book
  ☆115Updated last year
• PacktPublishing / EngineeringMLOps
  Engineering MLOps, published by Packt
  ☆183Updated 2 years ago
• maxhumber / DE4DS
  ⭕️ Data Engineering for Data Scientists
  ☆77Updated 2 years ago
• PacktPublishing / Machine-Learning-Algorithms-Second-Edition
  Machine Learning Algorithms Second Edition, published by Packt
  ☆61Updated last year
• dvaughan79 / analyticalskillsbook
  Code for the book Analytical Skills for AI and Data Science
  ☆47Updated 4 years ago
• PipelineAI / katacoda-notebooks
  O'Reilly Katacoda
  ☆56Updated 2 years ago
• DrDub / artfeateng
  Code for the book Art of Feature Engineering
  ☆31Updated 3 years ago
• MaartenGr / UnitTesting
  Guide for applying Unit Testing in data-driven projects
  ☆19Updated 4 years ago
• AutoViML / deep_autoviml
  Build tensorflow keras model pipelines in a single line of code. Now with mlflow tracking. Created by Ram Seshadri. Collaborators welcome…
  ☆121Updated 11 months ago