A collection of resources for pandas (Python) and related subjects.

Updated 2023-08-18 20:34:19 +08:00

Sample and simple code sharing for Capital Budgeting with Monte Carlo Simulation

Updated 2023-08-18 20:10:19 +08:00

Set of Jupyter notebook supporting articles on https://medium.com/@vdekanovsky

Updated 2023-09-15 10:43:33 +08:00

IPython notebooks with demo code intended as a companion to the book: Data Driven Science & Engineering: Machine Learning, Dynamical Systems, and Control by S. L. Brunton and J. N. Kutz http://databookuw.com/

Updated 2023-08-18 19:52:40 +08:00

Microsoft offer a 10-week, 20-lesson curriculum all about Data Science

Updated 2023-08-15 18:51:26 +08:00

These samples demonstrate how to use the DOcplex library to model and solve optimization problems.

Updated 2023-09-15 11:15:00 +08:00

A summary from a Chinese author "bitcarmanlee". Chinese contents. Please go to the author's link https://github.com/bitcarmanlee/easy-algorithm-interview-and-practice

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Get power generation from ZeverSolar Inverter and present it to front end as a sensor for Hass.IO

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Published by Packt, Hands-on Supervised Machine Learning with Python

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IBM Decision Optimization Tutorials for Python

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Repo that relates to the Medium blog 'Keeping your ML model in shape with Kafka, Airflow' and MLFlow'

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Inventory Management using Python. From https://github.com/wiredtoserve

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sql magic for IPython, hopefully evolving into full SQL client. http://catherinedevlin.blogspot.com/

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Jupylet is a Python library for programming 2D and 3D games, graphics, music and sound synthesizers, interactively in a Jupyter notebook. It is intended for three types of audiences: Computer scientists, researchers, and students of deep reinforcement learning. Musicians interested in sound synthesis and live music coding. Kids and their parents interested in learning to program.

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Lean Six Sigma (LSS) is a method based on a stepwise approach to process improvements.This approach usually follows 5 steps (Define, Measure, Analyze, Improve and Control) for improving existing process problems with unknown causes. source: https://github.com/samirsaci/lss-logistic-regression

Updated 2023-09-15 11:16:05 +08:00

ML for Trading - 2nd Edition This book aims to show how ML can add value to algorithmic trading strategies in a practical yet comprehensive way. It covers a broad range of ML techniques from linear regression to deep reinforcement learning and demonstrates how to build, backtest, and evaluate a trading strategy driven by model predictions.

Updated 2023-09-15 11:16:05 +08:00

MachineLearningStocks is designed to be an intuitive and highly extensible template project applying machine learning to making stock predictions. Source from: https://github.com/robertmartin8/MachineLearningStocks Caution!!! As of Feb 2021: MachineLearningStocks is no longer actively maintained

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Build a simple methodology of Supply Chain Network Design that is considering the fluctuation of the demand.

Updated 2023-09-15 11:15:00 +08:00