Data Analytics
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Dive into the world of Data Analytics – uncover insights, explore trends, and master data-driven decision making.

Admin: @HusseinSheikho || @Hussein_Sheikho
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πŸ“Œ How to Forecast Time Series Data with Python Darts

✍️ Adejumo Ridwan Suleiman
🏷️ #data_visualization
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πŸ“Œ Common Pitfalls to Avoid When Analyzing and Modeling Data

✍️ Oyedele Tioluwani
🏷️ #data_analysis
πŸ“Œ Master Technical Interviews by Learning Data Structures and Algorithms

✍️ Beau Carnes
🏷️ #data_structures
A comprehensive summary of the Seaborn Library.pdf
3.3 MB
πŸ“Š A comprehensive summary of the Β«Seaborn LibraryΒ»

πŸ‘¨πŸ»β€πŸ’» One of the best choices for any data scientist to convert data into clear and beautiful charts, so that they can better understand what the data is saying and also be able to present the results correctly and clearly to others, is the Seaborn library.

βœ… A very user-friendly library for creating professional charts with minimal coding. It is built on top of Matplotlib but is simpler and easier to use than that.

✏️ With this summary, you will learn the syntax, see many examples and real applications of #Seaborn, and ultimately help you elevate your #datavisualization skills by several levels.

🌐 #Data_Science #DataScience

https://xn--r1a.website/DataAnalyticsX 🌟

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Numpy @CodeProgrammer.pdf
2.4 MB
🏷 Sections of the «NumPy» library
⬅️ From introductory to advanced


πŸ‘¨πŸ»β€πŸ’» This is a long-term project to learn Python and NumPy from scratch. The main task is to handle numerical #data and #arrays in #Python using NumPy, and many other libraries are also used.


✏️ This section shows a structured and complete path for learning #NumPy; but the code examples and exercises help to practically memorize the concepts.


⭕️ Introduction to NumPy
🟠 NumPy arrays
⭕️ Introduction to array features
🟠 Basic operations on arrays
⭕️ Functions for statistical and aggregative purposes
🟠 And...

https://xn--r1a.website/CodeProgrammer β›ˆβš‘οΈ
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🐱 5 of the Best GitHub Repos
πŸ”ƒ for Data Scientists

πŸ‘¨πŸ»β€πŸ’» When I was just starting out and trying to get into the "data" field, I had no one to guide me, nor did I know what exactly I should study. To be honest, I was confused for months and felt lost.

▢️ But doing projects was like water on fire and helped me a lot to build my skills.

γ€° Repo Awesome Data Analysis

🏷 A complete treasure trove of everything you need to start: SQL, Python, AI, data analysis, and more... In short, if you want to start from zero and strengthen your foundation, start here first.

                  
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γ€° Repo Data Scientist Handbook

🏷 A concise handbook that tells you what you need to learn and what you can ignore for now.

                  
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γ€° Repo Cookiecutter Data Science

🏷 A standard project template used by professionals. With this template, you can structure your data analysis and AI projects like a pro.

                  
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γ€° Repo Data Science Cookie Cutter

🏷 This is also a very clean project template that teaches you how to build a data project that won’t fall apart tomorrow and can be easily updated. Meaning your projects will be useful in the real world from the start.

                  
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γ€° Repo ML From Scratch

🏷 Here, the main AI algorithms are implemented from scratch in simple language. It’s great for understanding how models really work and for explaining them well in your interviews.

🌐 #Data_Science #DataScience
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