AI Doctor Kit
by binginagesh 
Updated: Nov 2, 2021
Solution Kit
AI Doctor
IDE ENV AI Doctor
Libraries for Development Environment
notebookby jupyter
9901 Version:v7.0.0a18Jupyter Interactive Notebook
notebookby jupyter
Jupyter Notebook 9901 Version:v7.0.0a18 License: Permissive (BSD-3-Clause)
EDA
Libraries needed for exploratory data analysis and visualization
pandasby pandas-dev
37439 Version:v2.0.0rc1Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
pandasby pandas-dev
Python 37439 Version:v2.0.0rc1 License: Permissive (BSD-3-Clause)
matplotlibby matplotlib
17111 Version:v3.7.1
License: No License (null)matplotlib: plotting with Python
matplotlibby matplotlib
Python 17111 Version:v3.7.1 License: No License
numpyby numpy
23036 Version:v1.24.2The fundamental package for scientific computing with Python.
numpyby numpy
Python 23036 Version:v1.24.2 License: Permissive (BSD-3-Clause)
seabornby mwaskom
10513 Version:v0.12.2Statistical data visualization in Python
seabornby mwaskom
Python 10513 Version:v0.12.2 License: Permissive (BSD-3-Clause)
Modelling
Libraries needed for building models
scikit-learnby scikit-learn
53572 Version:1.2.2scikit-learn: machine learning in Python
scikit-learnby scikit-learn
Python 53572 Version:1.2.2 License: Permissive (BSD-3-Clause)
imbalanced-learnby scikit-learn-contrib
6285 Version:0.10.0A Python Package to Tackle the Curse of Imbalanced Datasets in Machine Learning
imbalanced-learnby scikit-learn-contrib
Python 6285 Version:0.10.0 License: Permissive (MIT)
imbalanced-learnby wqw547243068
0 Version:CurrentPython module to perform under sampling and over sampling with various techniques.
imbalanced-learnby wqw547243068
Python 0 Version:Current License: Others (Non-SPDX)
xgboostby dmlc
23912 Version:v1.7.4Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow
xgboostby dmlc
C++ 23912 Version:v1.7.4 License: Permissive (Apache-2.0)
Group Name 4
Kit Solution Source
buildwithai-hackathonby nagi1995
0 Version:Current License: No License (null)buildwithai-hackathonby nagi1995
Jupyter Notebook 0 Version:Current License: No License
Deployment Information
The simplest installation procedure would be to use anaconda (Can be downloaded from https://www.anaconda.com/). Create an virtual environment using conda create --name activate clone the GitHub repository git clone https://github.com/nagi1995/buildwithai-hackathon.git cd buildwithai-hackathon Use the below command to download necessary libraries for running the code pip install -r requirements.txt