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INTRODUCTION Machine Learning is a subset of Artificial Intelligence that enables systems to learn from data, identify patterns, and make decisions with minimal human intervention. It powers applications like recommendations and automation.
WHY CHOOSE? • 01 • 02 • Scalability – Easily handles large and growing datasets. • Continuous Improvement – Models improve with more data and feedback.
WHAT WILL YOU LEARN? • Model Evaluation – Techniques like accuracy, precision, recall, and confusion matrix. • Data Preprocessing - Cleaning and preparing data for modeling. • Real-World Projects – Applying ML to solve actual problems.
01 • 02 • 03 BENEFITS OF MACHINE LEARNING • Faster Decision Making – Speeds up complex decision processes. • Career Opportunities – High demand for skilled ML professionals across industries. • Scalability – Easily handles vast amounts of data as it grows.
TOOLS OF MACHINE LEARNING • Pandas – Data manipulation and analysis made easy. • Python – Most widely used language for ML development. • Google Colab – Cloud-based notebook with free GPU for ML experiments.
CAREER OPPORTUNITY • Data Scientist – Analyzes complex data to extract insights using ML techniques. • Deep Learning Engineer – Specializes in neural networks and deep learning systems. • Research Analyst – Uses ML for market, scientific, or academic research.
FUTURE SCOPE • Career Demand – Continuous rise in job opportunities with high salaries and global scope. • Advancements in AI – ML will power smarter AI systems with human-like capabilities.
CONCLUSION • Machine Learning enables systems to learn from data, improving accuracy and efficiency. It drives innovation across industries, offers vast career opportunities, and shapes the future of intelligent technology.
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