- Basic Definition of Machine Learning
- Types of machine Learning
- Hypothesis Space and bias
- Evaluation and Cross-validation
- Linear Regression
- Decision Trees and Questions-Answers
What you'll learn
- Theoretical concept of Machine learning
- Concepts of Regression
- Concepts of data preprocessing
- Overall Machine Learning theory and its algorithms
Description
The course introduces the concepts of Machine Learning. It covers the regression, both linear and logistic. Decision trees, Data preprocessing etc., to explore the machine learning in brief with plenty of examples. it also discusses the concept of state space, bias, etc. in Machine learning. Machine learning is the field of study that gives computers the ability to learn without being explicitly programmed. This course covers the following aspects of machine learning:
1.Basic Definitions 2.Types of Learning
3.Hypothesis space and Inductive Bias
4.Evaluation
5.Cross-Validation
6.Linear Regression
7.Decision Trees 8.Overfitting
The course is designed after studying the syllabus of various technological universities. Machine learning is basically of three types: The main goal in supervised learning is to learn a model from labeled training data that allows us to make predictions about unseen or future data. Supervised refers to a set of samples where the desired output signals (labels) are already known.
Unsupervised learning deals with unlabeled data or data of unknown structure. Using unsupervised learning techniques explores the structure of our data to extract meaningful information without the guidance of a known outcome variable or reward function.
In reinforcement learning, the goal is to develop a system (agent) that improves its performance based on interactions (reward signals) with the environment.
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About the instructors
- 3.95 Calificación
- 1496 Estudiantes
- 1 Cursos
Aniruddha Rumale
Dr. A S Rumale, Ph.D. CSE-Cloud, ME Comp, MBA HR, BE CSE
Dr. Aniruddha S Rumale is having 25+ years of academic experience in Computer Engineering, Information Technology, and Artificial intelligence.
At present, he is working as a Professor in the Information Technology Department at Sandip Foundation's Sandip Institute of Technology & Research centre, Nashik, an autonomous Institute affiliated to Savitribai Phule Pune University, Pune, India.
Dr. Rumale has expertise in computer programming languages like LaTeX, Java, Python, C++, and C, etc; Web Technologies like HTML, CSS, JS, etc. He taught many courses like Advance Algorithms, Artificial Intelligence, Data Science, Machine Learning, Computer Architecture, RDBMS, and so on...
He authored more than 4 books and 42 research papers in cloud Computing, Image Processing. He is having YouTube channel @TutorASRumale dedicated to technology and @rumalebhaktidhara dedicated to spirituality and Indian darshan.
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very poor quality in audio and content explanation