Basics of Machine Learning and It' limitations
Basics of Machine Learning and It' limitations, available at $49.99, has an average rating of 5, with 7 lectures, based on 15 reviews, and has 17 subscribers.
You will learn about You will learn basic of Machine Learning concepts You will learn limitations of machine learning You will learn Reinforcement Learning in Machine Learning You will learn Unsupervised learning in Machine Learning This course is ideal for individuals who are If you want to learn Web development, this course will be helpful for you. It is particularly useful for If you want to learn Web development, this course will be helpful for you.
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Summary
Title: Basics of Machine Learning and It' limitations
Price: $49.99
Average Rating: 5
Number of Lectures: 7
Number of Published Lectures: 7
Number of Curriculum Items: 7
Number of Published Curriculum Objects: 7
Original Price: $189.99
Quality Status: approved
Status: Live
What You Will Learn
- You will learn basic of Machine Learning concepts
- You will learn limitations of machine learning
- You will learn Reinforcement Learning in Machine Learning
- You will learn Unsupervised learning in Machine Learning
Who Should Attend
- If you want to learn Web development, this course will be helpful for you.
Target Audiences
- If you want to learn Web development, this course will be helpful for you.
You will learn the Machine Learning in this course. Machine Learning is a subset of artificial intelligence that focuses on the development of algorithms capable of learning from and making predictions based on data. It is a transformative technology that is redefining industries by enabling computers to perform tasks without explicit programming. At its core, machine learning involves feeding large amounts of data into algorithms, which then analyze the data to identify patterns and make informed decisions.
Unsupervised learning, on the other hand, deals with unlabeled data. The algorithm tries to identify patterns and relationships within the data without any prior knowledge of what the outputs should be. Clustering and association are typical tasks for unsupervised learning. For instance, a retailer might use an unsupervised learning algorithm to group customers into different segments based on purchasing behavior, which can then inform marketing strategies.
Reinforcement learning is a type of machine learning where an agent learns to make decisions by taking actions in an environment to maximize some notion of cumulative reward. Machine learning is a powerful tool that enables computers to learn from data and make decisions. Its applications are vast and varied, offering significant advancements across industries. As data continues to grow exponentially, the role of machine learning in solving complex problems and driving innovation will only become more critical.
Course Curriculum
Chapter 1: Introduction
Lecture 1: Introduction
Lecture 2: Limitations of Machine Learning
Lecture 3: The Importance of Machine Learning
Lecture 4: Reinforcement Learning
Lecture 5: Semi Supervised Learning
Lecture 6: Role of Machine Learning Expert
Lecture 7: Real Life examples of Machine Learning
Instructors
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Durga Prasad Chodavarapu
Web Design Engineer
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- 5 stars: 15 votes
Frequently Asked Questions
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