Derek Snow

DeltaPy - Tabular Data Augmentation (by @firmai)

Python solutions to solve practical business problems.

Machine Learning in Asset Management (by @firmai)

A curated list of practical financial machine learning tools and applications.

A curated, auto-updated directory of machine learning tools and resources for finance and trading, covering deep learning, NLP, reinforcement learning, portfolio optimization, and alternative data sources.

PandaPy has the speed of NumPy and the usability of Pandas 10x to 50x faster (by @firmai)

AtsPy: Automated Time Series Models in Python (by @firmai)

A curated list of applied machine learning and data science notebooks and libraries across different industries (by @firmai)

A curated directory of machine learning and data science code notebooks organized by industry sector, linking to practical Python examples for healthcare, banking, agriculture, retail, and a dozen more fields.

Google Colaboratory Notebooks and Repositories (by @firmai)

Career Resources for Data Science, Machine Learning, Big Data and Business Analytics Career Repository

A curated list of practical business machine learning (BML) and business data science (BDS) applications for Accounting, Customer, Employee, Legal, Management and Operations (by @firmai)

Advanced Pandas Vault — Utilities, Functions and Snippets (by @firmai).

DataGene - Identify How Similar TS Datasets Are to One Another (by @firmai)

ICR - Automated and Intelligent Company Report Built in Python (by @firmai)

Advanced Business Analytics and Mathematics with Python (by @firmai)

Time-series Generative Adversarial Networks (fork from the ML-AIM research group on bitbucket))

Scrapers from a project in 2018. Yelp, Spyfu, Similarweb, Morningstar, Linkedin, Instagram, Inside, Glassdoor, Facebook, Eat24, Doordash, Angellist.

MTSS-GAN: Multivariate Time Series Simulation with Generative Adversarial Networks (by @firmai)

Jupyter Notebook and Python business intelligence tools and techniques. [Raw upload]

FairPut - Machine Learning Fairness Framework with LightGBM — Explainability, Robustness, Fairness (by @firmai)

Notebooks based on financial machine learning.

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Code for Machine Learning for Algorithmic Trading, 2nd edition.

A selection of business datasets

Open Business Analytics and Data Science Research

A directory of the top business machine learning vendors

A look at regulatory challenges and recommendation in the age of AI. Investigating topics like monopoly formation, machine learning auditability, bias mitigation strategies and automated regulatory monitoring.

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A tutorial demonstrating how to implement deep learning models for time series forecasting

Reddit Data Science Project Ideas

Some course contents

Quant/Algorithm trading resources with an emphasis on Machine Learning

Simple Machine Learning and Data Science Definitions without Copyright

MlFinlab helps portfolio managers and traders who want to leverage the power of machine learning by providing reproducible, interpretable, and easy to use tools.

Numpy for Finance Examples

A curated list of insanely awesome libraries, packages and resources for Quants (Quantitative Finance)

🔬 A curated list of awesome machine learning strategies & tools in financial market.

Courses, Articles and many more which can help beginners or professionals.

A Collection of Cross-Sectional and Time-Series Generators

Advanced Transformations and Interactions for Linear Models using Hybrid Machine Learning Models and SHapley Additive exPlanations

XAIB - Explainable AI in Business

Weekly Quant Finance Seminars

Collection of algorithms for online portfolio selection

List of awesome resources for machine learning-based algorithmic trading

Multiple implementations for abstractive text summurization , using google colab

Functions used in kaggle competitions: data preprocessing/feature engineering/model training etc. Many of these functions are collected from kaggle community, credits are belong to the authors :)

Time-series machine learning at scale. Built with Polars for embarrassingly parallel feature extraction and forecasts on panel data.

Financial PDE Discovery using Machine Learning

Dataset Statistics to Compare Real or Training Data with Generated or Test Data

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FirmAI Labs - World's First Google Colab Website

ImputeGAP: A library of Imputation Techniques for Time Series Data

FFOOD - Framework for Feature and Observation Outlier Detection using ML-based Residual Analysis Methods

Website

A repository of experimental statistical techniques that improve on "well-accepted" solutions.

github profile readme

A comprehensive set of fairness metrics for datasets and machine learning models, explanations for these metrics, and algorithms to mitigate bias in datasets and models.

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Allows users to scrape select web pages and upload them to S3 bucket.

:love_letter: Things I've learned about writing good READMEs.

Dataset introduced in the paper "Zero-Shot Open Information Extraction using Question Generation and Reading Comprehension"

Fast Vectorised NumPy Functions for Finance

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Introduction to Data Science course project

Helper Functions

Analyzing free apps in the Google Play store and the App store to see which kind would be profitable for a company.

Shapley Feature Engineering

This page presents a list of satellite imagery datasets with a temporal dimension, mainly satellite image time series (SITS) and satellite videos, for various computer vision and deep learning tasks. It covers multi-temporal datasets with more than two acquisitions but not bi-temporal datasets.

Zoomable, animated scatterplots in the browser that scales over a billion points

Abuse of Google Colab for fun and profit. 🐧

Data Point Selection for Line Chart Visualization: analysis notebooks and implementation details

This application, developed in Python, helps you to choose the right place for open a new office, based on the preferences of the company's workers.

Source code for Multicriteria Portfolio Construction with Python

An easy to use blogging platform, with enhanced support for Jupyter Notebooks.

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AI Asset Management Research

My profile README repo. Share some love with a :star:!

Hey 👋, Glad to see you here! Check out this repository to learn more about me 🤓. You can also use it to make your awesome GitHub README ✨ (Don't Just Fork, Star Too 😅)

Analyzing the Customer database of a clothing brand and finding relation between dependent parameters and amount spent. Also analyzing, which area the company should focus on.

Balancing Algorithms for Stochastic Inventory Control

Code for our NeurIPS 2019 paper "Shape and Time Distortion Loss for Training Deep Time Series Forecasting Models"

Automatic extraction of relevant features adapted for DeltaPy

Medium Contributor Guidelines

A Python package that implements model-agnostic pre-and post-processing to mitigate unfairness in machine learning prediction

Forked template from Christoph Molnar, testing out website integration

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A Benchmark Dataset for Multimodal Scientific Fact Checking

One-year PD models that combine structural and ML methods in Python

Backend for DevJobs. This is where the magic happens.

🎬 Open-source solution to find the latest SWE jobs that are easy to apply

Performance analysis of predictive (alpha) stock factors

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Star / Fork badges for your GitHub Repository!

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My personal repo.

My GitHub README 📜 updated automatically using actions ⚡!

Traffic to badge action usage template. Use repositories Insights/traffic data to generate badges that include views and clones.

Dynamic realtime profile ReadMe linked with spotify

✨ uwa, special ✨

A readme with github actions generated statistics

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If you are forking please do not forget to star the repo

Profile with dynamic realtime coding stats. Please star if you like it!

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GitHub Profile README.md

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Long Articles

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FairXGB - Fair eXplainable Gradient Boosting Method

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TAIB - Trustable AI in Business

A public available dataset for using market sentiment for financial asset allocation.

Zindi Challenge for Sendy Logistics Company in Nairobi Final Submissions

To create a market mix model for ElecKart (an e-commerce firm from Ontario, Canada) for several products categories - to observe the actual impact of various marketing variables over the past and recommend the optimal budget allocation for different marketing levers for the next year. Built several Linear Regression models like Additive, Multiplicative, Koyck & Distributive Lag to identify the important KPIs that influence the company revenue and their contributions towards the revenue. The main data set is available below:

Theoretical Scenario: Finding the best markets to advertise in as an e-learning company offering courses in programming.

To place the 'new company offices' in the best place for the company to grow.

This is the data challenge held by Walter P Moore, which an international company providing engineering services. The data is their detailed project information in time series manner and the goal is to predict the profitability of a project

I cleaned over 125 columns and curated final 25 relevant columns, for the model used XG Boost + Hyperparameter + Standard Scaler to classify and predict mental health at work. The dataset were real survey from apprx 1000 workers in Tech Companies.

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