Ravena O

Python is incredibly versatile, ideal for data science, web development, and more. Here are some top libraries across different domains:

🔴 Data Manipulation

Pandas: Essential for data analysis.
NumPy: Great for arrays and matrices.
Vaex: Handles big datasets efficiently.
Polars: Fast DataFrame library in Rust.

🔴 Data Visualization

Matplotlib: Classic plotting.
Seaborn: Beautiful statistical graphics.
Plotly: Interactive graphs.
Bokeh: Web-friendly plots.

🔴 Statistical Analysis

SciPy: For scientific computing.
Statsmodels: Key for statistical models.

🔴 Machine Learning

Scikit-learn: Easy ML tools.
TensorFlow: Comprehensive ML platform.
PyTorch: Flexible deep learning.
XGBoost: Optimized boosting.

🔴 NLP

NLTK: Comprehensive NLP toolkit.
spaCy: Fast and robust NLP.
Gensim: Topic modeling.

🔴 Database Ops

Dask: Parallel computing.
PySpark: Big data processing.
Koalas: Pandas-like on Spark.

🔴 Time Series

Statsmodels: For time series analysis.
Prophet: Easy forecasting.

🔴 Web Scraping

Beautiful Soup: Simple scraping.
Scrapy: Powerful web crawling.
Selenium: Browser automation.

Explore these libraries to unlock Python’s potential. Happy coding!

#Python #DataScience #Programming #WebDevelopment

CC : Alex Wang

I have been constantly asked for a roadmap for various types of Data Professional roles. Though there is no same answer for everyone. Here are some courses to help you in your journey ⤵ ⤵ ⤵ ⤵⤵

1️⃣ 🧮 𝗠𝗮𝘁𝗵𝗲𝗺𝗮𝘁𝗶𝗰𝘀 & 𝗦𝘁𝗮𝘁𝗶𝘀𝘁𝗶𝗰𝘀:
• Linear Algebra, Calculus, and Probability & Statistics:
  https://lnkd.in/eabKGp_p
• OpenIntro Statistics -
  https://lnkd.in/eQvjgbmB

2️⃣ 🔯 𝗦𝗤𝗟 & 𝗗𝗮𝘁𝗮𝗯𝗮𝘀𝗲𝘀 :
• https://lnkd.in/ea2DmZ2d
  
3️⃣🤖 𝗖𝗼𝗿𝗲 𝗖𝗼𝗻𝗰𝗲𝗽𝘁𝘀 𝗼𝗳 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴:
• Google's ML Crash Course -
  https://lnkd.in/eT7NiGp6
• Andrew Ng's Coursera ML Course -
  https://lnkd.in/e964AiC7
• Fast.ai's Practical Deep Learning -
  https://course.fast.ai/

4️⃣ 💻 𝗣𝗿𝗼𝗴𝗿𝗮𝗺𝗺𝗶𝗻𝗴 𝗦𝗸𝗶𝗹𝗹𝘀 (𝗣𝘆𝘁𝗵𝗼𝗻 & 𝗟𝗶𝗯𝗿𝗮𝗿𝗶𝗲𝘀):
• Corey Schafer's Python Tutorials -
  https://lnkd.in/euyfHHxa
• Scikit-learn -
  https://lnkd.in/eqFhCwXt
• TensorFlow -
  https://lnkd.in/e6RWbe9h
• PyTorch -
  https://lnkd.in/efhPxZPM

5️⃣ 🎛️ 𝗠𝗼𝗱𝗲𝗹 𝗧𝗿𝗮𝗶𝗻𝗶𝗻𝗴 & 𝗧𝘂𝗻𝗶𝗻𝗴 𝗧𝗲𝗰𝗵𝗻𝗶𝗾𝘂𝗲𝘀:
• Kaggle's Intermediate ML -
  https://lnkd.in/e89AmkzE
• Hyperparameter Tuning -
  https://lnkd.in/ezEnqeG2

6️⃣ 🧠 𝗔𝗱𝘃𝗮𝗻𝗰𝗲𝗱 𝗗𝗲𝗲𝗽 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗠𝗼𝗱𝗲𝗹𝘀:
• Stanford's CS231n (CNNs) -
  http://cs231n.github.io/
• Deep Learning Book -
  https://lnkd.in/e_utEgZM

7️⃣ 🌐 𝗗𝗲𝗽𝗹𝗼𝘆𝗺𝗲𝗻𝘁, 𝗠𝗼𝗻𝗶𝘁𝗼𝗿𝗶𝗻𝗴, & 𝗠𝗮𝗶𝗻𝘁𝗲𝗻𝗮𝗻𝗰𝗲:
• Docker -
  https://lnkd.in/esXHzx9k
• Git -
  https://lnkd.in/esQ8FMxS
• AWS ML -
  https://lnkd.in/eZcdQPee
• Azure ML -
  https://lnkd.in/e5fvmvtk

8️⃣ 📝 𝗥𝗲𝘀𝘂𝗺𝗲 𝗣𝗿𝗲𝗽𝗮𝗿𝗮𝘁𝗶𝗼𝗻 ,𝗦𝗼𝗳𝘁 𝗦𝗸𝗶𝗹𝗹𝘀 & 𝗧𝗶𝗽𝘀 :
• Resume
  https://lnkd.in/eP7isRZF
• Soft Skills & Tips:
  https://lnkd.in/e_xE4wdr

9️⃣ 🎯 𝟮𝟭𝟳 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗣𝗿𝗼𝗷𝗲𝗰𝘁𝘀:
• https://lnkd.in/e5kyv3Tv