AI, IOT AND MACHINE LEARNING BASICS

ARTIFICIAL INTELLIGENCE IN HEALTHCARE: ADVANTAGES AND DISADVANTAGES

Explainable AI (XAI): Making Machine Learning Models Interpretable and Trustworthy Cloud Computing

NATURAL LANGUAGE PROCESSING (NLP) FOR DATA

NLP (NATURAL LANGUAGE PROCESSING) IN BIOINFORMATICS HEALTHCARE APPLICATIONS

INTERPRETABLE AI: TECHNIQUES FOR MAKING MACHINE LEARNING MODELS TRANSPARENT

MACHINE LEARNING EXPLAINED: A PRACTICAL GUIDE TO DATA-DRIVEN DECISION MAKING

DATA SCIENCE ETHICS AND RESPONSIBLE AIEITHICAL CONSIDERATIONS IN DATA SCIENCE AND AI

MACHINE LEARNING: APPLICATION AND CHALLENGES

DEEP LEARNING FOR DATA MINING UNSUPERVISED FEATURE LEARNING AND REPRESENTATION

APPLICATIONS BEYOND CRYPTOCURRENCIES - NON-FINANCIAL USE CASES FOR BLOCKCHAIN TECHNOLOGY

DATA STRUCTURES FOR MODERN APPLICATIONS

Internet of Things (IoT): Principles and Applications in Engineering

DEEP LEARNING FOR DATA MINING: UNSUPERVISED FEATURE LEARNING AND REPRESENTATION

MACHINE LEARNING APPLICATIONS

MACHINE LEARNING MASTERY: ALGORITHMS, APPLICATIONS AND INSIGHTS

PRACTICAL MACHINE LEARNING APPLICATIONS

AI AND ROBOTICS: A SYMBIOTIC RELATIONSHIP

MACHINE LEARNING FOR DATA SCIENCE - USING ML ALGORITHMS FOR PREDICTIVE MODELING

UNLEASHING THE POWER OF AI: A COMPREHENSIVE GUIDE TO ADVANTAGES AND DISADVANTAGES IN DIFFERENT INDUSTRIES