Deep Learning roadmap. Now it’s your turn!

𝗣𝗵𝗮𝘀𝗲 𝟭: 𝗡𝗲𝘂𝗿𝗮𝗹 𝗡𝗲𝘁𝘄𝗼𝗿𝗸 𝗙𝗼𝘂𝗻𝗱𝗮𝘁𝗶𝗼𝗻𝘀 (𝗪𝗲𝗲𝗸 𝟭-𝟮)
● Understand perceptrons, sigmoid, ReLU, tanh
● Learn cost functions, gradient descent, and derivatives
● Implement binary logistic regression using NumPy

𝗣𝗵𝗮𝘀𝗲 𝟮: 𝗦𝗵𝗮𝗹𝗹𝗼𝘄 𝗡𝗲𝘂𝗿𝗮𝗹 𝗡𝗲𝘁𝘄𝗼𝗿𝗸𝘀 (𝗪𝗲𝗲𝗸 𝟯-𝟰)
● Build a neural net with one hidden layer
● Compare activation functions (sigmoid vs tanh vs ReLU)
● Train your model to classify simple images

𝗣𝗵𝗮𝘀𝗲 𝟯: 𝗗𝗲𝗲𝗽 𝗡𝗲𝘂𝗿𝗮𝗹 𝗡𝗲𝘁𝘄𝗼𝗿𝗸𝘀 (𝗪𝗲𝗲𝗸 𝟱-𝟲)
● Forward and backward propagation through multiple layers
● Parameter initialization and tuning
● Implement L-layer neural networks from scratch

𝗣𝗵𝗮𝘀𝗲 𝟰: 𝗢𝗽𝘁𝗶𝗺𝗶𝘇𝗮𝘁𝗶𝗼𝗻 & 𝗥𝗲𝗴𝘂𝗹𝗮𝗿𝗶𝘇𝗮𝘁𝗶𝗼𝗻 (𝗪𝗲𝗲𝗸 𝟳-𝟴)
● Learn mini-batch gradient descent, RMSProp, and Adam
● Apply L2 and Dropout regularization to avoid overfitting
● Boost your model’s performance with better convergence

𝗣𝗵𝗮𝘀𝗲 𝟱: 𝗧𝗲𝗻𝘀𝗼𝗿𝗙𝗹𝗼𝘄 & 𝗥𝗲𝗮𝗹 𝗣𝗿𝗼𝗷𝗲𝗰𝘁𝘀 (𝗪𝗲𝗲𝗸 𝟵-𝟭𝟬)
● Build models using TensorFlow and Keras
● Normalize data, tune hyperparameters, and visualize metrics
● Create multi-class classifiers using softmax

𝗣𝗵𝗮𝘀𝗲 𝟲: 𝗥𝗲𝗮𝗹-𝗪𝗼𝗿𝗹𝗱 𝗣𝗿𝗼𝗷𝗲𝗰𝘁𝘀 & 𝗖𝗮𝗿𝗲𝗲𝗿 𝗣𝗿𝗲𝗽 (𝗪𝗲𝗲𝗸 𝟭𝟭-𝟭𝟮)
● Work on image recognition, text classification, and real datasets
● Learn model deployment techniques
● Prepare for interviews with hands-on projects and GitHub repo

https://t.me/CodeProgrammer ✉️

🚀 Model Context Protocol (MCP) Curriculum for Beginners

Learn MCP with Hands-on Code Examples in C#, Java, JavaScript, Python, and TypeScript
🧠 Overview of the Model Context Protocol Curriculum

The Model Context Protocol (MCP) is an innovative framework designed to standardize communication between AI models and client applications. This open-source curriculum provides a structured learning path, featuring practical coding examples and real-world scenarios across popular programming languages such as C#, Java, JavaScript, TypeScript, and Python.

Whether you're an AI developer, system architect, or software engineer, this guide is your all-in-one resource for mastering MCP fundamentals and implementation techniques.

Resources: https://github.com/microsoft/mcp-for-beginners/blob/main/translations/en/README.md

https://t.me/CodeProgrammer ⭐️

LangExtract

A Python library for extracting structured information from unstructured text using LLMs with precise source grounding and interactive visualization.

GitHub: https://github.com/google/langextract

https://t.me/DataScienceN 🖕