ADVANCEDMACHINE LEARNINGTECHNIQUES
INTRODUCTION TO ADVANCED ML TECHNIQUES
KEY TECHNIQUE: NEURAL NETWORKS WITH MANY LAYERS (E.G., CNNS FOR IMAGE RECOGNITION, RNNS FOR SEQUENCES).
APPLICATIONS: IMAGE RECOGNITION, NLP, SELF-DRIVING CARS.
REINFORCEMENT LEARNING
Concept:Learningthroughtrialanderror withrewardsandpenalties
Applications:Robotics,gameAI(e.g., AlphaGo),autonomoussystems Poppins UNSUPERVISED LEARNING
Techniques:Clustering(K-means), dimensionalityreduction(PCA),anomaly detection
Applications:Customersegmentation, frauddetection,datacompression
TRANSFER LEARNING
Concept:Fine-tuningpretrainedmodelsfornewtasks.
Applications:Medicalimaging, languagetranslation
