All Data Science Libraries: Tutorial

A list of all data science libraries with their tutorial using Python.

If you are learning Python for data science, you should know that there are many Python libraries that you should learn for data science. From reading a CSV file, or image dataset, to training your machine learning model, or a neural network, if you are using Python, many Python libraries will help you in the complete process of data science. So if you want to learn all Data Science libraries in Python, this article is for you. In this article, I will present you with a tutorial on all Data Science libraries.

All Data Science Libraries

Below is the list of all the Data Science libraries in Python that you need to learn:

Data Handling:

  1. Numpy
  2. Important Pandas Functions
  3. Pypolars

Data Visualization:

  1. Matplotlib
  2. Plotly
  3. PandasGUI
  4. Klib
  5. Matplotlib
  6. Plotly
  7. Folium
  8. VisualKeras

Web Scraping:

  1. PyScrappy
  2. Pandas Datareader
  3. Instaloader
  4. BeautifulSoup

Natural Language Processing:

  1. TextBlob
  2. NLTK
  3. Spacy

Machine Learning:

  1. Lazy Predict
  2. AutoTS
  3. PyCaret
  4. Facebook Prophet
  5. Scikit-learn
  6. MindsDB
  7. Streamlit

Deep Learning:

  1. AutoKeras
  2. NeuralProphet
  3. FastAI
  4. PyTorch
  5. TensorFlow

As Python is an open-source programming language, the above list of data science libraries will be regularly updated with more libraries.

Summary

So these were all the Python libraries you need to learn for data science. The above list of data science libraries will be updated with more tutorials every month. I hope you liked this article on a tutorial on all Data Science libraries in Python. Please feel free to ask your valuable questions in the comments section below.

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