TRANSFORMER NEURAL NETWORK From Mathematical Equations to MATLAB Code

To Support : https://www.paypal.com/paypalme/alshi... 🚀 TRANSFORMERS in MATLAB from Scratch! | Predict [1,2,3,4,5,6] → 7 with Attention Is All You Need In this comprehensive tutorial, we build a Transformer neural network entirely from mathematical first principles in MATLAB – no black boxes, no shortcuts. Then we compare it with MATLAB's built-in transformer layers to see how much easier real-world implementation can be. 🔢 What you'll learn: ✔️ The complete Transformer architecture (Encoder-Only for regression) ✔️ Positional Encoding – why sine/cosine waves give order to attention ✔️ Self-Attention – the "Attention Is All You Need" core equation ✔️ Multi-Head Attention – how parallel heads learn different relationships ✔️ Feed-Forward Networks & Residual "Add & Norm" connections ✔️ Full training loop with gradient descent from scratch ✔️ Direct comparison: 350 lines of math vs 35 lines of built-in layers 📂 Code & Resources: 🔹 Manual Transformer (full math) – included in the video 🔹 Built-in version: https://github.com/matlab-deep-learni... 🔹 MATLAB Transformer documentation: https://mathworks.com/help/deeplearni... 📖 Recommended Reading: • "Attention Is All You Need" – Vaswani et al. (2017) • "Machine and Deep Learning Using MATLAB" – Kamal I. M. Al-Malah (covers Transformers) 💡 Who this is for: • MATLAB users who want to understand deep learning internals • Students learning Transformer architectures • Quantitative finance / time-series forecasters • Anyone tired of "magic black boxes" – we write every equation! codes: https://github.com/alshikhkhalil/Tran... 🔔 Subscribe for more MATLAB deep learning tutorials: [Your Channel Link] 👍 Like if you learned something new – it helps the channel a lot! 💬 Questions? Drop them in the comments. I read every single one. #MATLAB #Transformer #DeepLearning #AttentionIsAllYouNeed #TimeSeriesPrediction #MachineLearning #FromScratch