ChatGPT going personal 😂

Hey guys,

Here are some best Telegram Channels for free education in 2025
👇👇

Free Courses with Certificate

Web Development Free Resources

Data Science & Machine Learning

Programming Free Books

Python Free Courses

Ethical Hacking & Cyber Security

English Speaking & Communication

Stock Marketing & Investment Banking

Coding Projects

Jobs & Internship Opportunities

Crack your coding Interviews

Udemy Free Courses with Certificate

ChatGPT Prompts

AI Projects

Free access to all the Paid Channels
👇👇
https://t.me/addlist/4q2PYC0pH_VjZDk5

Do react with ♥️ if you need more content like this

ENJOY LEARNING 👍👍

Waiting for that HR

Who is looking for DeepSeek expert with 5 years of experience. 😅😂

AI vs ML vs Neural Network vs Deep Learning ✅

Data Science Roadmap ✅

If I were to start my Machine Learning career from scratch (as an engineer), I'd focus here (no specific order):

1. SQL
2. Python
3. ML fundamentals
4. DSA
5. Testing
6. Prob, stats, lin. alg
7. Problem solving

And building as much as possible.

How to revolutionize Hollywood with AI.

Unlock new possibilities:

1. Voice Cloning

Clone voices of Hollywood icons:

• Legally clone and use voices with permission.
• Recreate iconic voices for new projects.
• Preserve legendary performances for future generations.

2. Custom Voices

Create unique voices for your projects:

• Generate up to 20 seconds of dialogue.
• Select from preset voice options or create your own.

3. Lip Sync Tool

Bring still characters to life:

• Use ElevenLabs's Lip Sync tool.
• Select a face and add a script.
• Generate videos with synchronized lip movements.

AI is reshaping the industry, voice cloning is part of a broader trend.

Filmmakers can now recreate voices of iconic actors.

Developer: I trained AI. (2015) ✅

AI: Now I train you. (2024) 😂🔥

Free AI Resources: 👇
https://lnkd.in/dyEZQwXv

Machine Learning Algorithms & Time Complexity

Should we worry or relax 😂

Machine Learning Roadmap 👆

🏆 – AI/ML Engineer

Stage 1 – Python Basics
Stage 2 – Statistics & Probability
Stage 3 – Linear Algebra & Calculus
Stage 4 – Data Preprocessing
Stage 5 – Exploratory Data Analysis (EDA)
Stage 6 – Supervised Learning
Stage 7 – Unsupervised Learning
Stage 8 – Feature Engineering
Stage 9 – Model Evaluation & Tuning
Stage 10 – Deep Learning Basics
Stage 11 – Neural Networks & CNNs
Stage 12 – RNNs & LSTMs
Stage 13 – NLP Fundamentals
Stage 14 – Deployment (Flask, Docker)
Stage 15 – Build projects

ENJOY LEARNING 👍👍

Emotional damage 😂