Team Vector - AI & ML with Java

🤖 AI & ML Contents (Java + OOP + DSA)

1. Core Java – Variables, Loops, Arrays, Collections, Exception Handling
2. OOPs Concepts – Classes, Objects, Inheritance, Polymorphism, Abstraction, Encapsulation
3. Data Structures & Algorithms – Arrays, Linked List, Stack, Queue, Trees, Graphs, HashMap, Searching, Sorting, Dynamic Programming
4. Math Foundation – Linear Algebra, Probability, Statistics, Calculus for AI
5. Data Handling in Java – JDBC, File Handling, JSON, XML, CSV
6. AI Concepts – Search Algorithms, Knowledge Representation, Expert Systems, Reasoning
7. Machine Learning (Java) – Regression, Classification, Clustering, Decision Trees, Random Forests
8. ML Libraries in Java – Weka, Smile, Deeplearning4j
9. Neural Networks & Deep Learning – Perceptron, CNNs, RNNs, LSTMs (using DL4J)
10. Natural Language Processing (NLP) – Text Processing, Tokenization, Sentiment Analysis, Chatbots
11. Computer Vision – Image Processing, Object Detection, Face Recognition (OpenCV with Java)
12. Reinforcement Learning – Q-learning, Markov Decision Processes, Game AI
13. Big Data + AI – Hadoop, Spark MLlib (Java API), Kafka
14. Cloud AI – Deploy AI models on AWS, GCP, Azure
15. Projects – AI Chatbot, Recommendation System, Image Classifier, Fraud Detection, Stock Prediction