Contents
- 1 What are the best sources to learn machine learning?
- 2 Which is the best book for machine learning beginners?
- 3 What is the most popular machine learning algorithm?
- 4 Who are the authors of Python for machine learning?
- 5 What is the basic concept of machine learning?
- 6 How is machine learning used in predictive data analytics?
What are the best sources to learn machine learning?
Best 7 Machine Learning Courses in 2021:
- Machine Learning — Coursera.
- Deep Learning Specialization — Coursera.
- Machine Learning Crash Course — Google AI.
- Machine Learning with Python — Coursera.
- Advanced Machine Learning Specialization — Coursera.
- Machine Learning — EdX.
- Introduction to Machine Learning for Coders — Fast.ai.
Which is the best book for machine learning beginners?
7 Great Books About Machine Learning (ML) For Beginners
- “Machine Learning For Absolute Beginners: A Plain English Introduction (Second Edition)” by Oliver Theobald.
- “Machine Learning For Dummies” by John Paul Mueller and Luca Massaron.
What is the most popular machine learning algorithm?
Top Machine Learning Algorithms You Should Know
- Linear Regression.
- Logistic Regression.
- Linear Discriminant Analysis.
- Classification and Regression Trees.
- Naive Bayes.
- K-Nearest Neighbors (KNN)
- Learning Vector Quantization (LVQ)
- Support Vector Machines (SVM)
Who is father of machine learning?
Geoffrey Hinton
| Geoffrey Hinton CC FRS FRSC | |
|---|---|
| Scientific career | |
| Fields | Machine learning Neural networks Artificial intelligence Cognitive science Object recognition |
| Institutions | University of Toronto Google Carnegie Mellon University University College London University of California, San Diego |
Which is the best book for machine learning?
Machine learning is also being widely used in several research projects that contribute towards making things a bit easier. The author duo Andreas C. and Sarah Guido has successfully delivered a compilation of some of the best practical applications to implement ML.
You’ll learn the steps necessary to create a successful machine-learning application with Python and the scikit-learn library. Authors Andreas Müller and Sarah Guido focus on the practical aspects of using machine learning algorithms, rather than the math behind them.
What is the basic concept of machine learning?
The basic concept of machine learning is that it starts with feeding the data into an algorithm and then it will allow machines to learn and eventually, get the desired result. It is neatly mentioned on the book cover using a pictorial representation.
How is machine learning used in predictive data analytics?
Fundamentals of Machine Learning for Predictive Data Analytics: Algorithms, Worked Examples, and Case Studies (MIT Press) “This introductory textbook offers a detailed and focused treatment of the most important machine learning approaches used in predictive data analytics, covering both theoretical concepts and practical applications.