An Ultimate Compilation of AI Resources for Mathematics, Machine Learning and Deep Learning. Highly recommended!
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A collection of resources for pandas (Python) and related subjects.
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Sample and simple code sharing for Capital Budgeting with Monte Carlo Simulation
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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/
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Microsoft offer a 10-week, 20-lesson curriculum all about Data Science
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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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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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Build a simple methodology of Supply Chain Network Design that is considering the fluctuation of the demand.
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PyPortfolioOpt is a library that implements portfolio optimization methods, including classical mean-variance optimization techniques and Black-Litterman allocation
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Material for a beginner Python course during 2019/2020
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Python basic study with Jupyter Notebook From https://github.com/wiredtoserve/datascience/tree/master/Python
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This repository contains the entire Python Data Science Handbook, in the form of (free!) Jupyter notebooks. https://jakevdp.github.io/PythonDataScienceHandbook/
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Jupyter notebooks from the scikit-learn video series Youtube link: https://www.youtube.com/playlist?list=PL5-da3qGB5ICeMbQuqbbCOQWcS6OYBr5A
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Find the optimal locations of your manufacturing facilities to meet your customers’ demand and reduce production costs. From Samir Saci
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This handbook extensively covers time series analysis and forecasting, delving from the most fundamental methods to the state-of-the-art. The handbook was made in Python and is designed such that readers can both learn the theory and apply them to real-world problems.
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Download market data from Yahoo! Finance's API
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