By continuing you indicate that you have read and agree to our Terms of service and Privacy policy
AI Doctor
IDE ENV AI Doctor
Libraries for Development Environment
EDA
Libraries needed for exploratory data analysis and visualization
pandasby pandas-dev
Python 33259 Version:v1.4.1
Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
matplotlibby matplotlib
Python 15355 Version:v3.5.1
matplotlib: plotting with Python
matplotlibby matplotlib
Python 15355 Version:v3.5.1 License: No License
Modelling
Libraries needed for building models
scikit-learnby scikit-learn
Python 49728 Version:1.0.2
scikit-learn: machine learning in Python
scikit-learnby scikit-learn
Python 49728 Version:1.0.2 License: Permissive (BSD-3-Clause)
imbalanced-learnby scikit-learn-contrib
Python 5660 Version:0.9.0
A Python Package to Tackle the Curse of Imbalanced Datasets in Machine Learning
imbalanced-learnby scikit-learn-contrib
Python 5660 Version:0.9.0 License: Permissive (MIT)
imbalanced-learnby wqw547243068
Python 0 Version:Current
Python module to perform under sampling and over sampling with various techniques.
imbalanced-learnby wqw547243068
Python 0 Version:Current License: Others (Non-SPDX)
xgboostby dmlc
C++ 22464 Version:v1.6.0rc1
Scalable, 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++ 22464 Version:v1.6.0rc1 License: Permissive (Apache-2.0)
Group Name 4
Kit Solution Source
buildwithai-hackathonby nagi1995
Jupyter Notebook 0 Version:Current
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