Download market data from Yahoo! Finance's API
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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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code and data for the time series analysis video from YouTube channel: https://www.youtube.com/@ritvikmath
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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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Jupyter notebooks from the scikit-learn video series Youtube link: https://www.youtube.com/playlist?list=PL5-da3qGB5ICeMbQuqbbCOQWcS6OYBr5A
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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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Python basic study with Jupyter Notebook From https://github.com/wiredtoserve/datascience/tree/master/Python
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Material for a beginner Python course during 2019/2020
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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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Prompt engineering is a relatively new discipline for developing and optimizing prompts to efficiently use language models (LMs) for a wide variety of applications and research topics.
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It is an utility library for Kaggle and offline competitions. It is particularly focused on experiment tracking, feature engineering, and validation.
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Neural Networks: Zero to Hero
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Implementing a Neural Network from Scratch
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The simplest, fastest repository for training/finetuning medium-sized GPTs.
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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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https://github.com/karpathy/makemore makemore takes one text file as input, where each line is assumed to be one training thing, and generates more things like it.
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Large Language Model Course
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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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sql magic for IPython, hopefully evolving into full SQL client. http://catherinedevlin.blogspot.com/
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Inventory Management using Python. From https://github.com/wiredtoserve
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