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10 great Python packages for Data Science not known to many:
1️⃣ CleanLab
You're missing out on a lot if you haven't started using Cleanlab yet!
Cleanlab helps you clean data and labels by automatically detecting issues in a ML dataset.
It's like a magic wand! 🪄✨
Check this out👇
https://lnkd.in/dY2fp5YW
2️⃣ LazyPredict
A Python library that enables you to train, test, and evaluate multiple ML models at once using just a few lines of code.
Supports both regression & classification! ✨
Check this out👇
https://lnkd.in/ggZ-HByv
3️⃣ Lux
A Python library for quickly visualizing and analyzing data, providing an easy and efficient way to explore data.
Check this out👇
https://lnkd.in/genaV395
4️⃣ PyForest
A time-saving tool that helps in importing all the necessary data science libraries and functions with a single line of code.
Check this out👇
https://lnkd.in/gv2tsjMe
5️⃣ PivotTableJS
PivotTableJS lets you interactively analyse your data in Jupyter Notebooks without any code 🔥
Check this out👇
https://lnkd.in/dapGg-AS
6️⃣ Drawdata
Drawdata is a python library that allows you to draw a 2-D dataset of any shape in a Jupyter Notebook.
Very handy for learning & understanding the behaviour of ML algorithms!
Check this out👇
https://lnkd.in/gBSrQ-e4
7️⃣ black
The Uncompromising Code Formatter
Arguably the best, I use it everyday!!
Check this out 👇
https://lnkd.in/gsz2Mxqn
8️⃣ PyCaret
An open-source, low-code machine learning library in Python that automates the machine learning workflow.
Check this out👇
https://lnkd.in/gUzh-YZM
9️⃣ PyTorch-Lightning by @LightningAI⚡️
If you like PyTorch, you'll love PyTorch Lightning!
Streamlines your model training, automates boilerplate code, and lets you focus on what matters: research & innovation.
Check this out👇
https://lnkd.in/dir2Xej7
🔟 Reflex
Build Performant, customizable web apps in pure Python that you can deploy in seconds
Reflex is a library to build full-stack web apps in pure Python.
Check this out👇
https://lnkd.in/gz_vsNba
https://t.iss.one/CodeProgrammer🆘
1️⃣ CleanLab
You're missing out on a lot if you haven't started using Cleanlab yet!
Cleanlab helps you clean data and labels by automatically detecting issues in a ML dataset.
It's like a magic wand! 🪄✨
Check this out👇
https://lnkd.in/dY2fp5YW
2️⃣ LazyPredict
A Python library that enables you to train, test, and evaluate multiple ML models at once using just a few lines of code.
Supports both regression & classification! ✨
Check this out👇
https://lnkd.in/ggZ-HByv
3️⃣ Lux
A Python library for quickly visualizing and analyzing data, providing an easy and efficient way to explore data.
Check this out👇
https://lnkd.in/genaV395
4️⃣ PyForest
A time-saving tool that helps in importing all the necessary data science libraries and functions with a single line of code.
Check this out👇
https://lnkd.in/gv2tsjMe
5️⃣ PivotTableJS
PivotTableJS lets you interactively analyse your data in Jupyter Notebooks without any code 🔥
Check this out👇
https://lnkd.in/dapGg-AS
6️⃣ Drawdata
Drawdata is a python library that allows you to draw a 2-D dataset of any shape in a Jupyter Notebook.
Very handy for learning & understanding the behaviour of ML algorithms!
Check this out👇
https://lnkd.in/gBSrQ-e4
7️⃣ black
The Uncompromising Code Formatter
Arguably the best, I use it everyday!!
Check this out 👇
https://lnkd.in/gsz2Mxqn
8️⃣ PyCaret
An open-source, low-code machine learning library in Python that automates the machine learning workflow.
Check this out👇
https://lnkd.in/gUzh-YZM
9️⃣ PyTorch-Lightning by @LightningAI⚡️
If you like PyTorch, you'll love PyTorch Lightning!
Streamlines your model training, automates boilerplate code, and lets you focus on what matters: research & innovation.
Check this out👇
https://lnkd.in/dir2Xej7
🔟 Reflex
Build Performant, customizable web apps in pure Python that you can deploy in seconds
Reflex is a library to build full-stack web apps in pure Python.
Check this out👇
https://lnkd.in/gz_vsNba
https://t.iss.one/CodeProgrammer
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Forwarded from Data Science Machine Learning Data Analysis
📌 PyTorch Explained: From Automatic Differentiation to Training Custom Neural Networks
🗂 Category: DEEP LEARNING
🕒 Date: 2025-09-24 | ⏱️ Read time: 15 min read
Deep learning is shaping our world as we speak. In fact, it has been slowly…
🗂 Category: DEEP LEARNING
🕒 Date: 2025-09-24 | ⏱️ Read time: 15 min read
Deep learning is shaping our world as we speak. In fact, it has been slowly…
❤4👾2👨💻1
By: https://t.iss.one/CodeProgrammer
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Forwarded from Python | Machine Learning | Coding | R
This channels is for Programmers, Coders, Software Engineers.
0️⃣ Python
1️⃣ Data Science
2️⃣ Machine Learning
3️⃣ Data Visualization
4️⃣ Artificial Intelligence
5️⃣ Data Analysis
6️⃣ Statistics
7️⃣ Deep Learning
8️⃣ programming Languages
✅ https://t.iss.one/addlist/8_rRW2scgfRhOTc0
✅ https://t.iss.one/Codeprogrammer
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Forwarded from Data Science Machine Learning Data Analysis
📌 How to Build Effective Agentic Systems with LangGraph
🗂 Category: AGENTIC AI
🕒 Date: 2025-09-30 | ⏱️ Read time: 12 min read
Create AI workflows with agentic frameworks
🗂 Category: AGENTIC AI
🕒 Date: 2025-09-30 | ⏱️ Read time: 12 min read
Create AI workflows with agentic frameworks
Forwarded from Data Science Machine Learning Data Analysis
📌 A Basic Introduction to Quantum GANs
🗂 Category: MACHINE LEARNING
🕒 Date: 2024-09-21 | ⏱️ Read time: 11 min read
“Quantum computing just becomes vastly simpler once you take the physics out of it.”
🗂 Category: MACHINE LEARNING
🕒 Date: 2024-09-21 | ⏱️ Read time: 11 min read
“Quantum computing just becomes vastly simpler once you take the physics out of it.”
❤6
Today I am 3️⃣0️⃣ years old, I am excited to make more successes and achievements
My previous year was full of exciting events and economic, political and programmatic noise, but I kept moving forward
Best regards
Eng. @HusseinSheikho 🔤
My previous year was full of exciting events and economic, political and programmatic noise, but I kept moving forward
Best regards
Eng. @HusseinSheikho 🔤
1🎉20❤8🔥1
Harvard's "Advanced Algorithms"
by Jelani Nelson
📽 Lecture Videos: https://youtube.com/playlist?list=PL2SOU6wwxB0uP4rJgf5ayhHWgw7akUWSf
📷 Lecture Notes: https://people.seas.harvard.edu/~cs224/fall14/lec.html
https://t.iss.one/CodeProgrammer 👍
by Jelani Nelson
📽 Lecture Videos: https://youtube.com/playlist?list=PL2SOU6wwxB0uP4rJgf5ayhHWgw7akUWSf
📷 Lecture Notes: https://people.seas.harvard.edu/~cs224/fall14/lec.html
https://t.iss.one/CodeProgrammer 👍
❤5
Google Collab notebooks to learn everything you need to master prompt engineering with Claude - from basic structure and role prompting to advanced techniques like few-shot learning, avoiding hallucinations, and tool use.
Perfect interactive lessons to level up your AI skills
Link: https://github.com/anthropics/courses/tree/master/prompt_engineering_interactive_tutorial/Anthropic%201P
https://t.iss.one/CodeProgrammer
Perfect interactive lessons to level up your AI skills
Link: https://github.com/anthropics/courses/tree/master/prompt_engineering_interactive_tutorial/Anthropic%201P
https://t.iss.one/CodeProgrammer
❤6👍4
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This GitHub repository is a real treasure trove of free programming books.
Here you'll find hundreds of books on topics like #AI, #blockchain, app development, #game development, #Python #webdevelopment, #promptengineering, and many more✋
GitHub: https://github.com/EbookFoundation/free-programming-books
https://t.iss.one/CodeProgrammer⭐
Here you'll find hundreds of books on topics like #AI, #blockchain, app development, #game development, #Python #webdevelopment, #promptengineering, and many more
GitHub: https://github.com/EbookFoundation/free-programming-books
https://t.iss.one/CodeProgrammer
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Forwarded from Data Science Machine Learning Data Analysis
📌 Image Segmentation With K-Means Clustering
🗂 Category: MACHINE LEARNING
🕒 Date: 2024-09-05 | ⏱️ Read time: 11 min read
An introduction with Python
🗂 Category: MACHINE LEARNING
🕒 Date: 2024-09-05 | ⏱️ Read time: 11 min read
An introduction with Python
❤2👍1
Forwarded from Data Science Machine Learning Data Analysis
📌 A Guide to Clustering Algorithms
🗂 Category: DATA SCIENCE
🕒 Date: 2024-09-06 | ⏱️ Read time: 6 min read
An overview of clustering and the different families of clustering algorithms.
🗂 Category: DATA SCIENCE
🕒 Date: 2024-09-06 | ⏱️ Read time: 6 min read
An overview of clustering and the different families of clustering algorithms.
❤4
Forwarded from Data Science Jupyter Notebooks
Python library RetinaFace for face detection and working with key points (eyes, nose, mouth)
Supports face alignment, easily installed via
An excellent tool for tasks in computer vision and face recognition.
Usage examples:
👉 @DataScienceN
Supports face alignment, easily installed via
pip install retina-face
, and works based on deep models from the insightface project.An excellent tool for tasks in computer vision and face recognition.
Usage examples:
from retinaface import RetinaFace
resp = RetinaFace.detect_faces("img1.jpg")
print(resp)
{
"face_1": {
"score": 0.9993440508842468,
"facial_area": [155, 81, 434, 443],
"landmarks": {
"right_eye": [257.82974, 209.64787],
"left_eye": [374.93427, 251.78687],
"nose": [303.4773, 299.91144],
"mouth_right": [228.37329, 338.73193],
"mouth_left": [320.21982, 374.58798]
}
}
}
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Forwarded from Data Science Machine Learning Data Analysis
📌 How to Build a Genetic Algorithm from Scratch in Python
🗂 Category: DATA SCIENCE
🕒 Date: 2024-08-30 | ⏱️ Read time: 16 min read
A complete walkthrough on how one can build a Genetic Algorithm from scratch in Python,…
🗂 Category: DATA SCIENCE
🕒 Date: 2024-08-30 | ⏱️ Read time: 16 min read
A complete walkthrough on how one can build a Genetic Algorithm from scratch in Python,…
💯3
Forwarded from Data Science Machine Learning Data Analysis
📌 Extracting Structured Vehicle Data from Images
🗂 Category:
🕒 Date: 2025-01-27 | ⏱️ Read time: 10 min read
Build an Automated Vehicle Documentation System that Extracts Structured Information from Images, using OpenAI API,…
🗂 Category:
🕒 Date: 2025-01-27 | ⏱️ Read time: 10 min read
Build an Automated Vehicle Documentation System that Extracts Structured Information from Images, using OpenAI API,…
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Awesome interactive textbook on probability theory and statistics
Inside are clear visualizations, interactive elements, and minimal dry theory. You can tweak distributions, sample datasets, play with confidence intervals, and clearly see how it all works
Get it here, I recommend opening it on a desktop
https://seeing-theory.brown.edu/
👉 @DataScienceM
Inside are clear visualizations, interactive elements, and minimal dry theory. You can tweak distributions, sample datasets, play with confidence intervals, and clearly see how it all works
Get it here, I recommend opening it on a desktop
https://seeing-theory.brown.edu/
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Great find for developers: free cheat sheets on Deep Learning and PyTorch
A detailed guide to creating and training neural networks - link
Basic principles and practice of working with PyTorch - link
👉 @CODEPROGRAMMER
A detailed guide to creating and training neural networks - link
Basic principles and practice of working with PyTorch - link
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800+ SQL Server Interview Questions and Answers .pdf
1 MB
It also includes tasks for self-study and many examples.
The collection is perfect for those who want to improve their SQL skills, refresh their knowledge, and test themselves.
https://t.iss.one/addlist/8_rRW2scgfRhOTc0
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