Machine Learning Guide: Learn Machine Learning Algorithms
3.1 (183 ratings)
Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately.
10,028 students enrolled

Machine Learning Guide: Learn Machine Learning Algorithms

Machine Learning: A comprehensive guide to machine learning. Learn machine learning algorithms & machine learning tools
3.1 (183 ratings)
Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately.
10,028 students enrolled
Created by Grid Wire
Last updated 5/2019
English
English [Auto]
Current price: $129.99 Original price: $199.99 Discount: 35% off
22 hours left at this price!
30-Day Money-Back Guarantee
This course includes
  • 1 hour on-demand video
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
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What you'll learn
  • 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
Course content
Expand all 12 lectures 01:06:39
+ Core Concepts
2 lectures 14:51
Core Concepts (Part 1)
07:13
Core Concepts (Part 2)
07:38
+ Algorithms
6 lectures 35:24
Decision Trees
04:04
K-Means Clustering
04:02
K-Nearest Neighbor
04:05
Naive Bayes
04:07
Best Practices and Applications
15:00
Requirements
  • You'll need a desktop computer (Windows, Mac, or Linux).
  • No prior knowledge or experience needed. Only the desire to learn!
Description

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.

Who this course is for:
  • Developers
  • Technology consultants
  • Engineers
  • Computer scientists
  • Statisticians