🤖 Artificial Intelligence Roadmap 🧠
|-- Fundamentals
| |-- Mathematics
| | |-- Linear Algebra
| | |-- Calculus
| | |-- Probability & Statistics
| | └─ Discrete Mathematics
| |
| |-- Programming
| | |-- Python
| | |-- R (Optional)
| | └─ Data Structures & Algorithms
| |
| └─ Machine Learning Basics
| |-- Supervised Learning
| |-- Unsupervised Learning
| |-- Reinforcement Learning
| └─ Model Evaluation & Selection
|-- Supervised_Learning
| |-- Regression
| | |-- Linear Regression
| | |-- Polynomial Regression
| | └─ Regularization Techniques
| |
| |-- Classification
| | |-- Logistic Regression
| | |-- Support Vector Machines (SVM)
| | |-- Decision Trees
| | |-- Random Forests
| | └─ Naive Bayes
| |
| └─ Model Evaluation
| |-- Metrics (Accuracy, Precision, Recall, F1-Score)
| |-- Cross-Validation
| └─ Hyperparameter Tuning
|-- Unsupervised_Learning
| |-- Clustering
| | |-- K-Means Clustering
| | |-- Hierarchical Clustering
| | └─ DBSCAN
| |
| └─ Dimensionality Reduction
| |-- Principal Component Analysis (PCA)
| └─ t-distributed Stochastic Neighbor Embedding (t-SNE)
|-- Deep_Learning
| |-- Neural Networks Basics
| | |-- Activation Functions
| | |-- Loss Functions
| | └─ Optimization Algorithms
| |
| |-- Convolutional Neural Networks (CNNs)
| | |-- Image Classification
| | └─ Object Detection
| |
| |-- Recurrent Neural Networks (RNNs)
| | |-- Sequence Modeling
| | └─ Natural Language Processing (NLP)
| |
| └─ Transformers
| |-- Attention Mechanisms
| |-- BERT
| |-- GPT
|-- Reinforcement_Learning
| |-- Markov Decision Processes (MDPs)
| |-- Q-Learning
| |-- Deep Q-Networks (DQN)
| └─ Policy Gradient Methods
|-- Natural_Language_Processing (NLP)
| |-- Text Processing Techniques
| |-- Sentiment Analysis
| |-- Topic Modeling
| |-- Machine Translation
| └─ Language Modeling
|-- Computer_Vision
| |-- Image Processing Fundamentals
| |-- Image Classification
| |-- Object Detection
| |-- Image Segmentation
| └─ Image Generation
|-- Ethical AI & Responsible AI
| |-- Bias Detection and Mitigation
| |-- Fairness in AI
| |-- Privacy Concerns
| └─ Explainable AI (XAI)
|-- Deployment & Production
| |-- Model Deployment Strategies
| |-- Cloud Platforms (AWS, Azure, GCP)
| |-- Model Monitoring
| └─ Version Control
|-- Online_Resources
| |-- Coursera
| |-- Udacity
| |--
fast.ai
| |-- Kaggle
| └─ TensorFlow, PyTorch Documentation
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