Machine Learning Techniques Lecture 1 in Hinglish - Learning and Types of Machine Learning

In this lecture of the Machine Learning Techniques series, we explore the fundamental concept of learning in Machine Learning and understand how machines improve their performance through experience. The session introduces the formal definition of learning using Task (T), Experience (E), and Performance Measure (P), followed by a detailed discussion of the major types of Machine Learning. Topics Covered: Introduction to Learning in Machine Learning Learning from Experience: Task, Performance, and Experience Machine Learning Learning Problem Supervised Learning Labelled Data and Prediction Models Regression and Classification Real-World Applications of Supervised Learning Unsupervised Learning Pattern Discovery and Clustering Association Learning Applications of Unsupervised Learning Reinforcement Learning Agent–Environment Interaction Rewards and Penalties Applications in Robotics and Game Playing Comparison of Supervised, Unsupervised, and Reinforcement Learning Summary and Key Takeaways This lecture is designed for B.Tech, BCA, MCA, M.Tech, Data Science, Artificial Intelligence, and Machine Learning learners who want to build a strong foundation in ML concepts. Instructor: Dr. Bindeshwar Singh Kushwaha Associate Professor (AI/ML) Ambalika Institute of Management and Technology, Lucknow Connect with PostNetwork Academy: Website: [www.postnetwork.co](http://www.postnetwork.co) YouTube: [   / @postnetworkacademy  ](   / @postnetworkacademy  ) Facebook: [www.facebook.com/postnetworkacademy](  / postnetworkacademy  ) LinkedIn: [www.linkedin.com/company/postnetworkacademy](  / postnetworkacademy  ) GitHub: [www.github.com/postnetworkacademy](http://www.github.com/postnetworkacademy) #MachineLearning #ArtificialIntelligence #SupervisedLearning #UnsupervisedLearning #ReinforcementLearning #DataScience #MLTutorial #AITutorial #MachineLearningTechniques #PostNetworkAcademy #DeepLearning #AI