dynamic data science dashboard with Taipy Scenarios
This repository stores the code of a Full Stack GUI App Project featured in my Youtube tutorial.
taipy >= 4.0.0
(previous versions do no havetp.Orchestrator()
but usetp.Core()
instead)plotly == 5.24.1
tensorflow == 2.18.0
scikit-learn == 1.5.2
>> conda create env -n your_name python=3.11
>> conda activate your_name
>> pip install taipy
>> pip install plotly
>> pip install tensorflow
>> pip install scikit-learn
This enviropnment will result in obtaining predictions faster. How faster depends on your CPU and GPU model.
On my end, it results in approx. 20% speed up from switching to RTX 4080 GPU over 12th Gen Intel i9-12900k CPU.
*Please replace the first command with one that matches your system requirements and CUDA version from the official RAPIDS installation guide.
>> conda create -n your_name -c rapidsai -c conda-forge -c nvidia cudf=24.10 python=3.12 'cuda-version>=12.0,<=12.5'
>> conda activate your_name
>> pip install taipy
>> pip install plotly
>> pip install tensorflow
>> pip install scikit-learn
S&P 500 Stocks (daily updated) by Larxel
https://www.kaggle.com/datasets/andrewmvd/sp-500-stocks
Please checkout Taipy's Official Github Repo for more details and contribution guidelines.
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