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The Python libraries that I need to learn for competitive programming

The Python libraries that I need to learn for competitive programming

There are atleast 32 Python Libraries You need to learn to become a full fledged programmer are as follows.

Python Libraries Stands forfor Machine Learning (ML)TypesUsed for
Apriori
✔️ML AlgorithmMining frequent itemsets and devising association rules from a transactional database.
BeautifulSoup

Data Mining/ScrapingScraping data from web
Bokeh
✔️ML LibraryCreating interactive visualizations for modern web browsers
CaffeConvolutional Architecture for Fast Feature Embedding✔️ML FrameworkAcademic research projects
Core Python

Python LibraryIncludes all the core fucntionalities of python
DTsDecision Trees✔️ML AlgorithmClassification and regression
Eli5
✔️ML FrameworkInspect ML classifiers and explain their predictions
Hierarchical Clustering
✔️ML AlgorithmMethod to analyze social network data
Keras
✔️ML FrameworkCreating deep models which can be productized on smartphones & distributed training of deep learning models. Used by companies such as Netflix
K-Mean Clustering
✔️ML AlgorithmFind groups which have not been explicitly labeled in the data
KNNK-Nearest Neighbors✔️ML AlgorithmClassification (most commonly) and regression
LightGBMLight Gradient Boosting Machine✔️
Ranking
Linear Regression
✔️ML AlgorithmTo predict the value of a variable based on the value of another variable.
Logistic Regression
✔️ML AlgorithmUnderstand the relationship between the dependent variable and one or more independent variables by estimating probabilities using a logistic regression equation.
Matplotlib
✔️ML LibraryData visualization and graphical plotting library for Python and its numerical extension NumPy
Naive Bayes
✔️ML AlgorithmPredict the probability of different class based on various attributes.
NumpyNumerical Python✔️Math CalculationMath Calculation
PandasPython Data Analysis Library✔️Edit/View DataData analysis and associated manipulation of tabular data in Dataframes
Plotly
✔️Edit/View DataCreate beautiful interactive web-based visualizations on Jupyter Notebook.
PyCaret
✔️Machine LearningAutomates machine learning workflows
PyTorch
✔️ML FrameworkApplications of research
Random Forest
✔️Decision tree AlgorithmsClassification and regression problems
RegExRegular Expression
Python LibraryTo check if a string contains the specified search pattern.
SklearnScikit-learn✔️ML LibraryContains a lot of efficient tools for machine learning and statistical modeling including classification
SciPyScientific Python✔️Math CalculationUtility functions for optimization
Scrapy

Data Mining/ScrapingScrapy is a Python framework for large scale web scraping
Seaborn

Edit/View DataMaking statistical graphics in Python
SQLStructured Query Language
Edit/View DataManaging or querying data stored in a relational database management system (RDBMS).
SVMSupport Vector Machine✔️ML AlgorithmSupervised and linear Machine Learning algorithm. Solving classification problems
TensorFlow
✔️Python LibraryFast numerical computing created and released by Google.
Theano

Python LibraryFast numerical computation that can be run on the CPU or GPU.
XGBoostExtreme Gradient Boosting
Python LibraryProvides a wrapper class to allow models to be treated like classifiers or regressors in the scikit-learn framework.

Comments

  1. Nice write-up! To support the demand for Python app development, Python is very popular, and one of the most popular languages ​​for developers. Constantly, Python development company are growing rapidly with the increasing demand of Python web app development. Thanks for sharing! Keep sharing.

    ReplyDelete

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