Machine Learning
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Real Machine Learning — simple, practical, and built on experience.
Learn step by step with clear explanations and working code.

Admin: @HusseinSheikho || @Hussein_Sheikho
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Want any LLM to answer from your own documents?
Most RAG setups quietly give weak, vague answers, and the model is almost never the real problem. Three small fixes decide whether it works, and the exact tools to use in 2026 are very specific.
Full, concrete guide in one post.
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The guide Path to Senior Engineer Handbook has gathered resources for developers who want to advance to the level of Senior Engineer. 🚀

Inside: 📚

More than 50 newsletters on professional growth, system design, leadership, and web development. 📈

A selection of books on communication, technical writing, and building working relationships. 🤝

Selected YouTube channels, podcasts, and professional communities. 🎧

Courses, scientific articles, and educational platforms for a deeper study of topics. 🎓

A good starting point for those who want to improve not only their technical skills, but also their architectural thinking, communication, and leadership competencies. 💡

Link: https://github.com/jordan-cutler/path-to-senior-engineer-handbook?utm_source=opensourceprojects.dev&ref=opensourceprojects.dev

#SeniorEngineer #CareerGrowth #SoftwareEngineering #TechLeadership #SystemDesign #DevCommunity

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🚀 Level up your AI & Data Science skills with HelloEncyclo — a growing all-in-one platform featuring hands-on courses in LLMs, Deep Learning, MLOps, Data Engineering, and more.
13 courses live + 40+ coming soon
🎯 One access, lifetime updates
🔑 Use code: PRESALE-BOOK-WAVE-2GFG
👉 https://helloencyclo.com/?ref=HUSSEINSHEIKHO
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Classical machine learning equations and diagrams cheat sheet 📊

https://github.com/soulmachine/machine-learning-cheat-sheet

#MachineLearning #ML #DataScience #CheatSheet #AI #DeepLearning

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🚀 Level up your AI & Data Science skills with HelloEncyclo — a growing all-in-one platform featuring hands-on courses in LLMs, Deep Learning, MLOps, Data Engineering, and more.
13 courses live + 40+ coming soon
🎯 One access, lifetime updates
🔑 Use code: PRESALE-BOOK-WAVE-2GFG
👉 https://helloencyclo.com/?ref=HUSSEINSHEIKHO
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A free MIT guide to key computer vision concepts 📘

Link: https://visionbook.mit.edu/ 🔗

#ComputerVision #MIT #AI #MachineLearning #Tech #DataScience

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🚀 Level up your AI & Data Science skills with HelloEncyclo — a growing all-in-one platform featuring hands-on courses in LLMs, Deep Learning, MLOps, Data Engineering, and more.
13 courses live + 40+ coming soon
🎯 One access, lifetime updates
🔑 Use code: PRESALE-BOOK-WAVE-2GFG
👉 https://helloencyclo.com/?ref=HUSSEINSHEIKHO
1
My favorite way to work with multiple filters in pandas.Series — not a chain of .loc, but a single mask. 🐼

The chain looks neat, but breaks on real data and easily gives unexpected results:

s = pd.Series([10, 15, 20, 25, 30])
s.loc[s > 20].loc[s % 2 == 1]

The problem is that the second .loc again looks at the original s, not the already filtered result. The logic gets messy. 🤯

It's more reliable to gather everything into one expression:

s = pd.Series([10, 15, 20, 25, 30])

mask = (s > 20) & (s % 2 == 1)
result = s.loc[mask]

One mask, one point of truth.

It's easier to debug. Fewer surprises when the code grows. 🚀

#Pandas #Python #DataScience #CodingTips #DataEngineering #Debugging

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🚀 Level up your AI & Data Science skills with HelloEncyclo — a growing all-in-one platform featuring hands-on courses in LLMs, Deep Learning, MLOps, Data Engineering, and more.
13 courses live + 40+ coming soon
🎯 One access, lifetime updates
🔑 Use code: PRESALE-BOOK-WAVE-2GFG
👉 https://helloencyclo.com/?ref=HUSSEINSHEIKHO
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Multi-agent RL is beautiful precisely at the moment when it starts to converge. 🤖

#MultiAgent #RL #ReinforcementLearning #AI #MachineLearning #DeepLearning

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🚀 Level up your AI & Data Science skills with HelloEncyclo — a growing all-in-one platform featuring hands-on courses in LLMs, Deep Learning, MLOps, Data Engineering, and more.
13 courses live + 40+ coming soon
🎯 One access, lifetime updates
🔑 Use code: PRESALE-BOOK-WAVE-2GFG
👉 https://helloencyclo.com/?ref=HUSSEINSHEIKHO
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PANDAS — CHEAT SHEET
1. DATA LOADING
Method          | What it does       
----------------+--------------------
pd.read_csv() | Reads CSV file
pd.read_excel() | Reads Excel file
pd.read_sql() | Reads data from SQL
pd.read_json() | Reads JSON file

2. DATA ANALYSIS
Method        | What it does              
--------------+---------------------------
df.head() | Shows first rows
df.info() | Table information
df.describe() | Statistics by columns
df.shape | Table size (rows, columns)
df.columns | List of column names

3. DATA SELECTION
Method     | What it does                     
-----------+----------------------------------
df.loc[] | Selection by row and column names
df.iloc[] | Selection by indices
df.query() | Filtering by condition

4. DATA CLEANING
Method               | What it does                   
---------------------+--------------------------------
df.isnull() | Check for missing values (NULL)
df.dropna() | Remove rows with missing values
df.fillna() | Fill missing values
df.drop_duplicates() | Remove duplicates
df.astype() | Change data type

5. ANALYTICS
Method            | What it does               
------------------+----------------------------
df.groupby() | Data grouping
df.agg() | Aggregation in groups
df.value_counts() | Count of unique values
df.mean() | Mean value
df.median() | Median
df.corr() | Correlation between columns

6. DATA MERGING
Method      | What it does        
------------+---------------------
pd.merge() | SQL JOIN by column
pd.join() | JOIN by index
pd.concat() | Glue tables together

TOP 10 METHODS

read_csv() head() info() loc[] iloc[] query() groupby() merge() fillna() sort_values()
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500 AI/ML/Computer Vision/NLP projects with code 🚀

This is a large collection of 500 ready-made projects in the field of machine learning, deep learning, computer vision, and NLP 🧠

All examples come with code, so you can not just read them, but immediately analyze and run them ⚙️

➡️ Link to GitHub:
https://github.com/ashishpatel26/500-AI-Machine-learning-Deep-learning-Computer-vision-NLP-Projects-with-code

#AI #MachineLearning #DeepLearning #ComputerVision #NLP #DataScience

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There are hundreds of AI channels on YouTube. Here's why we made another one.

Most AI content does one of two things: it stays so surface-level it teaches you nothing, or it goes so deep you need a PhD to follow along.

We built Guidely for everyone in between.

→ We start with absolute beginners in mind
→ Then take you deeper, until the details actually click
→ Every guide is reviewed by experienced AI engineers
→ We don't make more content. We make better content.
Whether you build, design, or market products, our goal is simple: leave you thinking "I've never seen it broken down this well."

Two good places to start 👇

AI vs ML vs Deep Learning vs GenAI ... But Done Right!
The terms everyone uses. The distinctions are almost never explained clearly. We fix that: youtu.be/72yyLA2wRWc

How to Break into AI Engineering in 2026
A senior applied scientist shares what actually matters:  youtu.be/42vE7Ij4kdU

If AI has ever felt overwhelming or noisy, this channel is for you. If the content resonates with you, please don’t forget to like and subscribe.
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