valeman

Awesome_Math_Books.

awesome-conformal-prediction. A professionally curated list of awesome Conformal Prediction videos, tutorials, books, papers, PhD and MSc theses, articles and open-source libraries.

Transformers_And_LLM_Are_What_You_Dont_Need. The best repository showing why transformers might not be the answer for time series forecasting and showcasing the best SOTA non transformer models.

Awesome_CatBoost. The repository to showcase the best framework for tabular data - the Awesome CatBoost

Mastering-Modern-Time-Series-Forecasting-The-Complete-Guide. The repo for Mastering Modern Time Series Forecasting : The Complete Guide to Statistical, Machine Learning & Deep Learning Models in Python book https://valeman.gumroad.com/l/MasteringModernTimeSeriesForecasting

smote_is_what_you_dont_need. The best repository showing why SMOTE and resampling methods might not be the answer for imbalanced data problems

Multi-class-probabilistic-classification. Multi-class probabilistic classification using inductive and cross Venn–Abers predictors

bayesianism_is_what_you_dont_need. The best repo showing why bayesianism is a complete misnomer

calibration_is_what_you_need.

scikit-learn-is-what-you-dont-need. The best repo showing why scikit-learn is not what it seems also showing alternatives

VennABERS. Fast implementation of Venn-ABERS probabilistic predictors

TabPFN_Is_What_You_Dont_Need. The best repo showing why TabPFN doesn’t work.

awesome-kalman-filter. A curated list of awesome libraries, projects, tutorials, papers, and other resources related to Kalman Filter(KF). This repository aims to be a comprehensive and organized collection that will help researchers and developers in the world of KF!

TimeKAN. An offical implementation of "TimeKAN: KAN-based Frequency Decomposition Learning Architecture for Long-term Time Series Forecasting" (ICLR 2025)

Awesome-time-series-1.

cp-op. Replication of "Conformal prediction of option prices", 2024, Joao A. Bastos (https://doi.org/10.1016/j.eswa.2023.123087) with some extensions.

ml-for-finance. Jupyter Notebook

Modeva. Integrated tool for model development and validation

awesome-deep-time-series-representations. A curated list of state-of-the-art papers on deep learning for universal representations of time series.

TabKANet. TabKANet, Use Kolmogorov Arnold network and Transformer to unify tabular data modeling.

conformal-prediction-intro. Intro to Conformal prediction

Times2D. A novel time series forecasting method, Times2D, transforms 1D data into 2D space using multi-period decomposition and derivative heatmaps to achieve state-of-the-art performance.

MultiRocket. Multiple pooling operators and transformations for fast and effective time series classification

Awesome-Decision-Science. An evergrowing, professionally curated list of resources on everything decision-making: videos, tutorials, books, papers, theses, articles, datasets, and open-source libraries.

Time-Series-Forecasting-and-Deep-Learning. Resources about time series forecasting and deep learning.

CNN-KAN. A modified CNN architecture using Kolmogorov-Arnold Networks

conformal.glm. conformal prediction for generalized linear regression models

mSSA. Multivariate Singular Spectrum Analysis (mSSA): Forecasting and Imputation algorithm for multivariate time series

TQNet. [ICML 2025] Official repository of the TQNet paper: "Temporal Query Network for Efficient Multivariate Time Series Forecasting". This work is developed by the Lab of Professor Weiwei Lin (linww@scut.edu.cn), South China University of Technology; Pengcheng Laboratory.

pearsonify. Lightweight Python package for generating classification intervals in binary classification tasks using Pearson residuals and conformal prediction.

long-tail-conformal. Code release for "Conformal Prediction for Long-Tailed Classification"

Modern-Time-Series-Forecasting-with-Python-2E. Modern Time Series Forecasting with Python 2E, Published by Packt

linkedIn_auto_jobs_applier_with_AI. LinkedIn_AIHawk is a tool that automates the jobs application process on LinkedIn. Utilizing artificial intelligence, it enables users to apply for multiple job offers in an automated and personalized way.

plexe. ✨ Build a machine learning model from a prompt

Fourier. Python and MatLab code for Fourier transform book

conformal_prediction_and_beyond. Conformal prediction applied both to exchangeable and time-series data. Carried out as part of (UB 2023) MSc thesis work.

luigi. Luigi is a Python module that helps you build complex pipelines of batch jobs. It handles dependency resolution, workflow management, visualization etc. It also comes with Hadoop support built in.

Awesome_CQR.

M6_winning_solution. R

Awesome-TimeSeries-LLM-FM. The collection of resources about LLM for Time series tasks

Solar-Radiation-Forecasting. Code for Master's dissertation: Solar Radiation Forecasting with Deep Learning and Conformal Prediction

GLAFF. PyTorch implementation of "Rethinking the Power of Timestamps for Robust Time Series Forecasting: A Global-Local Fusion Perspective" (NeurIPS 2024)

FinTSB. FinTSB: A Comprehensive and Practical Benchmark for Financial Time Series Forecasting

Algorithmic_Trading_with_Python. This comprehensive, hands-on course provides a thorough exploration into the world of algorithmic trading, aimed at students, professionals, and enthusiasts with a basic understanding of Python programming and financial markets.

perpetual. A self-generalizing gradient boosting machine that doesn't need hyperparameter optimization

frouros. Frouros: an open-source Python library for drift detection in machine learning systems.

scikit-llm. Seamlessly integrate LLMs into scikit-learn.

FinanceDatabase. This is a database of 300.000+ symbols containing Equities, ETFs, Funds, Indices, Currencies, Cryptocurrencies and Money Markets.

timesfm. TimesFM (Time Series Foundation Model) is a pretrained time-series foundation model developed by Google Research for time-series forecasting.

UniTS. A unified time series model.

ETC3550Slides. Slides for a forecasting course based on "Forecasting: Principles and Practice"

SLCP. Conformal Prediction with Localized De-correlation

Awesome-Out-Of-Distribution-Detection. A professionally curated list of papers, tutorials, books, videos, articles and open-source libraries etc for Out-of-distribution detection, robustness, and generalization

SpringerML. Downloads free Machine Learning and Data books from Springer

Ensemble-Regularized-Adaptive-Prediction-Set-ERAPS. Official repository for the ICML 2022 DFUQ paper: conformal prediction sets for time-series

TS4CP. Code for enhancing Conformal Prediction using Temperature Scaling. Explore more of our work at:

preference-based-cp. Jupyter Notebook

RusTaLib. Technical Indicators Library, for time series data.

kaggle-past-time-series-competition.