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animator / learn-python

📖🐍 Free & Open Source book to master Python 3. Also available: PDF & Web Interface.
https://animator.github.io/learn-python/
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Add content: Python used in different applications #457

Closed Aditi22Bansal closed 4 months ago

Aditi22Bansal commented 4 months ago

I would like to add content about Python being used in different applications as listed below.

  1. Introduction to Pandas and NumPy
  2. Data Visualization with Matplotlib, Seaborn, and Plotly
  3. Machine Learning Basics with Scikit-Learn
  4. Deep Learning with TensorFlow and PyTorch
  5. Natural Language Processing with NLTK and SpaCy
  6. Time Series Analysis with Prophet and statsmodels
  1. Metaprogramming
  2. Concurrency and Parallelism
  3. Design Patterns in Python
  4. Optimizing Python Code
  5. Python Internals
  1. Django Deep Dive
  2. Flask Microservices
  3. FastAPI
  4. GraphQL with Python
  5. Real-time Applications with WebSockets
  1. Web Scraping with Beautiful Soup, Scrapy, and Selenium
  2. Automating Office Tasks with openpyxl, python-docx, and PyPDF2
  3. System Administration with Paramiko and Fabric
  4. APIs and Bots

I have some amazing content on this Please assign this issue to me and add labels

AnshitaSingh123 commented 4 months ago

I am proficient in Python language and am well versed with all its applications. Please assign this task to me. Given Python's versatility and widespread use, I believe highlighting its applications will add significant value. Python's role spans numerous domains, including:

  1. Web Development: With frameworks like Django and Flask, Python simplifies the creation of robust web applications.
  2. Data Science and Machine Learning: Python is the go-to language for data analysis, visualization, and machine learning, with libraries such as Pandas, Matplotlib, and TensorFlow.
  3. Automation and Scripting: Python excels in automating repetitive tasks, making it a favorite among DevOps engineers and system administrators.
  4. Software Development: From developing standalone applications to integrating systems, Python's simplicity and readability enhance productivity.
  5. Scientific Computing: Libraries like NumPy and SciPy enable complex scientific computations, driving advancements in research and engineering. I am confident that my background in Python and my passion for clear, engaging writing will ensure that this new content is both informative and accessible. I look forward to the opportunity to create detailed, compelling sections on these applications.
animator commented 4 months ago

Choose a single small section for which you will be contributing and raise a new issue.