AI & ML

AI & ML Blog – Complete Roadmap

AI & ML Blog – Complete Content Roadmap

A Structured Plan to Cover All Major AI & Machine Learning Topics

Part 1 – Foundations of AI & ML

1. Introduction to AI & ML

What is Artificial Intelligence?
What is Machine Learning?
History & Evolution of AI
Types of AI (Narrow, General, Super AI)
Real-world Applications

2. Essential Mathematics

Linear Algebra
Calculus
Probability & Statistics
Optimization Techniques

3. Programming Skills

Python Fundamentals
NumPy, Pandas, Matplotlib
Scikit-Learn
Jupyter Notebook & Google Colab

Part 2 – Core Machine Learning

Major Algorithms

Algorithm	Type	Use Case
Linear Regression	Supervised	Predict continuous values
Logistic Regression	Supervised	Binary classification
Decision Trees	Supervised	Classification
Random Forest	Ensemble	High accuracy classification
K-Means	Unsupervised	Clustering
SVM	Supervised	Classification

Part 3 – Deep Learning & Advanced AI

Neural Networks

Perceptron
Forward & Backpropagation
Activation Functions
Cost Functions

Deep Learning Frameworks

Framework	Description
TensorFlow	Google’s Deep Learning Platform
PyTorch	Popular for Research
Keras	High-level Neural Network API

Part 4 – Major AI Domains

Natural Language Processing (NLP)
Computer Vision
Reinforcement Learning

Part 5 – Major AI Platforms & Tools

AI Platform	Description
OpenAI (ChatGPT)	Conversational AI & Large Language Models
Google AI	AI Tools & Cloud ML Services
Microsoft Azure AI	Enterprise AI Services
IBM Watson	Business AI Platform
AWS AI Services	Cloud-based ML Solutions
Hugging Face	Transformer Models & NLP Tools
Anthropic Claude	Safety-focused AI Assistant
Meta AI (LLaMA)	Open Research Transformer Models

Learning Timeline

Beginner (Weeks 1–4)

AI Basics
Python Programming
Math for ML

Intermediate (Weeks 5–10)

Supervised & Unsupervised Learning
Model Evaluation
Projects

Advanced (Weeks 11–20)

Deep Learning
NLP & Transformers
Computer Vision
Reinforcement Learning

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