4.15 out of 5
4.15
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Machine Learning Guide: Learn Machine Learning Algorithms

Machine Learning: A comprehensive guide to machine learning. Learn machine learning algorithms & machine learning tools
Instructor:
Grid Wire
3,504 students enrolled
English [Auto-generated]
Fundamental concepts of AI and applications of machine learning
Learn different classification and regression techniques
Learn clustering, including k-means and k-nearest Neighbors
Learn Decision Trees to decode classification
Learn Regression analysis to create trend lines
Understand Bias/Variance to improve your machine learning model

Artificial Intelligence is becoming progressively more relevant in today’s world. The rise of AI has the potential to transform our future more than any other technology. By using the power of algorithms, you can develop applications which intelligently interact with the world around you, from building intelligent recommender systems to creating self-driving cars, robots and chatbots.

Machine learning is one of the most important areas of Artificial Intelligence. Machine learning provides developing methods that can automatically detect patterns in data and then use the uncovered patterns to predict future data. It can be applied across many industries to increase profits, reduce costs, and improve customer experiences.

In this course I’m going to provide you with a comprehensive introduction to the field of machine learning. You will learn how to build predictive models by extracting patterns from large datasets. These models are used in predictive data analytics applications including price prediction, risk assessment, predicting customer behavior, and document classification. Also i’m going to offer you a detailed and focused treatment of the most important machine learning approaches used in predictive data analytics. You’ll discover how to make informed decisions about which algorithms to use, and how to apply them to real-world scenarios. In addition you’ll learn how to drive innovation by combining data, technology and design to solve real problems at an enterprise scale.

This course is focused on helping you drive concrete business decisions through applications of artificial intelligence and machine learning. It makes the fundamentals and algorithms of machine learning accessible to students in statistics, computer science, mathematics, and engineering. This means plain-English explanations and no coding experience required. This is the best practical guide for business leaders looking to get true value from the adoption of machine learning technology.

Introduction

1
Introduction

Defining Machine Learning

1
Defining Machine Learning (Part 1)
2
Defining Machine Learning (Part 2)

Core Concepts

1
Core Concepts (Part 1)
2
Core Concepts (Part 2)

Algorithms

1
Decision Trees
2
K-Means Clustering
3
K-Nearest Neighbor
4
Naive Bayes
5
Regression
6
Best Practices and Applications

Conclusion

1
Conclusion
You can view and review the lecture materials indefinitely, like an on-demand channel.
Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don't have an internet connection, some instructors also let their students download course lectures. That's up to the instructor though, so make sure you get on their good side!
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Includes

1 hours on-demand video
Full lifetime access
Access on mobile and TV
Certificate of Completion