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AI: Machine Learning Techniques with Scala

Explore the most innovative and cutting edge machine learning techniques with Scala.

The ability to apply machine learning techniques to large datasets is becoming a highly sought-after skill in the world of technology. Scala can help you deliver key insights into your data—its unique capabilities as a language let you build sophisticated algorithms and statistical models. For this reason, machine learning and Scala fit together perfectly and knowledge of both would be beneficial for anyone entering the data science field.

In this course, you'll learn

  • Write Scala code implementing neural network models for prediction and clustering
  • Plot and analyze the structure of datasets with exploratory data analysis techniques using Scala
  • Use new and popular Scala frameworks such as Akka and Spark to implement machine learning algorithms and Scala libraries such as Breeze for numerical computing and plotting
  • Get to grips with the most popular machine learning algorithms used in the areas of regression, classification, clustering, dimensionality reduction, and neural networks
  • Use the power of MLlib libraries to implement machine learning with Spark
  • Work with the k-means algorithm and implement it in Scala with the real datasets
  • Get to know what dimensionality reduction is and explore the theory behind how the PCA algorithm works
  • Analyze and implement linear regression and GLMs in Scala and run them on real datasets
  • Use the Naive bayes algorithms and its methods to predict the probability of different classes based on various attributes
The course starts with a general introduction to the Scala programming language. From there, you’ll be introduced to several practical machine learning algorithms from the areas of exploratory data analysis. You’ll look at supervised learning machine learning models for prediction and classification tasks, and unsupervised learning techniques such as clustering and dimensionality reduction and neural networks.
By the end, you will be comfortable applying machine learning algorithms to solve real-world problems using Scala.


Course Curriculum


  Section 2 Exploratory Data Analysis with Scala
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Bill Gates Says These Are the Jobs He Would Drop Out of College for Today

If he were to go into computer sciences today, Gates said, the area that he thought had the most potential was artificial intelligence. Gates brought up a recent victory by Google DeepMind over the top player in the world at Go, a game some predicted a computer could never master. He called it a remarkable achievement that signaled there is more to come in advancement in artificial intelligence. And he said the research being done in the field now is "profound" and on the verge of making new breakthroughs. "The ability for artificial agents to read and understand material is going to be phenomenal," says Gates. "Anything connected with that would be an exciting lifetime career."

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Frequently Asked Questions


Why join this course?
Short answer - AI is fun, and it pays very well! Want to start a career in the exciting field of Deep Learning, Machine Learning, and Artificial Intelligence? This course is an excellent start. Yes, AI jobs pay a LOT more than regular programming jobs!
What if I don't know how to program?
No worries. We'll have you up and running in no time. And we'll step you through every single line of code as we go in case you get lost. If you have a familiarity with some high school mathematics, you're not going to have a problem learning this course with our help!
What devices are supported?
You can take the course from any device and any location, as long as you have an internet connection. All lectures are optimized for mobile or desktop viewing.
When does the course start and finish?
The course starts now and never ends! It is a completely self-paced online course - you decide when you start and when you finish.
How long do I have access to the course?
How does lifetime access sound? After enrolling, you have unlimited access to this course for as long as you like - across any and all devices you own.
What if I am unhappy with the course?
We would never want you to be unhappy! If you are unsatisfied with your purchase, contact us in the first 30 days and we will give you a full refund.

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