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AI Engineering
Introduction to AI
fundamentals of Ai
SuperVised Learning
UnsuperVised Learning
Reinforcement and learing
Evaluation Metrics
Overfitting and Underfitting
Programs & Mathematics
Python For Ai
Calculus & Linear Alegbra
Probability & Statistics
Databases & SQL
Data Structure & Algorithms
Numpy ,Pandas Matplotlib
Data Processing
Data Cleaning
Data Transformation
Data Integration
Handling Missing Data
Feature Engineering
Feature Scaling
Advanced ML Algorithms
Decision Tress & Random Forest
Regression Models
Support Vector Machines
K-Nearest Neighbors
Gradient Boosting Algorithms
Neural Networks
Deep Learning
Introduction to Neural Networks
Convolutional Neural Networks
Recurrent Neural Networks
Auto Encoders
Generative Adversarial Networks
Transfer Learning
Natural Language Process
Text Data Cleaning
Text Data Processing
Tokenization & Stemming
Bag Of Words & TF-IDF
Sentiment Analysis
ChatBot Development
Computer Vision
Image Processing Techniques
Object Detection
Image Segmentation
Face Recognition
OpenCV
Image Classification
Reinforcement Learning
The BellMan Equation
Markov Decision Processes
Policy & Value Iteration
Q-Learning
Sarsa
Deep Q Networks
Ethics & Laws In AI
Understanding Ai Ethics
Transparency&Accountability Ai
AI Surveillance
Data Privacy
Intellectual Property Right Ai
CyberSecurity In Ai
Ai Hardware & Software
CPU VS GPU In Ai
Cloud Computing Services For Ai
Frameworks & libraries Of Ai
Hardware For Ai
Deploying AI Models
Model Evaluation & Validation
Model Selection
Creating & Using APIs
Scalibility Considerations
Creating Docker Containers
Deploying To Cloud Services
Keeping Up-To Date
Reading AI Research Papers
Attending Ai Conferences
Open Source Ai Projects
New Tools & Techniques
Networking With Ai Professionals
Continuing Education With Ai
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For detailed explanations and theory, visit the
Complete Ai Engineering Roadmap Notes
.