Apress / modern-deep-learning-tabular-data

Related projects ⓘ

Alternatives and complementary repositories for modern-deep-learning-tabular-data

• atreadw1492 / software_engineering_for_data_scientists
  ☆10Updated last year
• gkunapuli / ensemble-methods-notebooks
  A collection of companion Jupyter notebooks for Ensemble Methods for Machine Learning (Manning, 2023)
  ☆71Updated last year
• jianzhnie / AutoTabular
  Automatic machine learning for tabular data. ⚡🔥⚡
  ☆68Updated 2 years ago
• lmassaron / Advanced_Analytics_for_Business
  Code for the new Manning book on machine learning on tabular datasets
  ☆11Updated 5 months ago
• PacktPublishing / The-Kaggle-Workbook
  Code Repository for The Kaggle Workbook, Published by Packt
  ☆113Updated last year
• marcopeix / TimeSeriesForecastingUsingFoundationModels
  Official repository for the book Time Series Forecasting with Foundation Models
  ☆10Updated last week
• PacktPublishing / Deep-Learning-for-Time-Series-Data-Cookbook
  B21145 - Deep Learning for Time Series Data Cookbook
  ☆42Updated 5 months ago
• valeman / Multi-class-probabilistic-classification
  Multi-class probabilistic classification using inductive and cross Venn–Abers predictors
  ☆43Updated 2 years ago
• ogrisel / euroscipy-2022-time-series
  Tutorial on time-series forcasting with scikit-learn
  ☆36Updated last year
• PacktPublishing / Accelerate-Deep-Learning-Workloads-with-Amazon-SageMaker
  Accelerate Deep Learning Workloads with Amazon SageMaker, published by Packt
  ☆16Updated last year
• Moffran / calibrated_explanations
  Repository for the explanation method Calibrated Explanations (CE)
  ☆53Updated this week
• probabl-ai / youtube-appendix
  Resources for some of our education content
  ☆30Updated last week
• cvs-health / aequilibrium
  Package designed for handling imbalanced classification
  ☆18Updated last year
• dataman-git / modern-time-series
  ☆35Updated 2 months ago
• smazzanti / valicast
  Validation for forecasts
  ☆18Updated last year
• Brett-Kennedy / ikNN
  An interpretable kNN based on aggregating the predictions of multiple 2d spaces.
  ☆12Updated last month
• atif-hassan / FRUFS
  An unsupervised feature selection technique using supervised algorithms such as XGBoost
  ☆88Updated 10 months ago
• ysraell / forecasting
  Forecasting: Principles and Practice
  ☆30Updated 3 years ago
• lmassaron / deep_learning_for_tabular_data
  A presention of core concepts and a data generator making easier using tabular data with TensorFlow and Keras
  ☆41Updated last year
• KishManani / m5-forecasting-tutorial
  An end-to-end tutorial to forecast the M5 dataset using feature engineering pipelines and gradient boosting.
  ☆15Updated last year
• jrzaurin / tabulardl-benchmark
  Benchmark tabular Deep Learning models against each other and other non-DL techniques
  ☆53Updated 3 years ago
• se-jaeger / conformal-data-cleaning
  Code for the AISTATS 2024 Paper "From Data Imputation to Data Cleaning - Automated Cleaning of Tabular Data Improves Downstream Predictiv…
  ☆19Updated 9 months ago
• Animadversio / TransformerFromScratch
  Tutorial for Harvard Medical School ML from Scratch Series: Transformer from Scratch. Demo the usage of transformer in various domains: M…
  ☆40Updated last year
• ben-arnao / StoRM
  A neural network hyper parameter tuner
  ☆29Updated 10 months ago
• solegalli / feature_engine
  Feature engineering package with sklearn like functionality
  ☆50Updated 2 months ago
• kylegallatin / ml-python-cookbook-runner
  Dockerized Jupyter notebook to run commands from the ML Python Cookbook
  ☆34Updated last year
• ElizaLo / Time-Series
  Awesome list and projects of Time Series
  ☆25Updated last year
• datamllab / automl-in-action-notebooks
  Jupyter notebooks for the code samples of the book "Automated Machine Learning in Action"
  ☆89Updated last year
• fastforwardlabs / structural-time-series
  Structural Time Series on US electricity demand data
  ☆23Updated 3 years ago