Projects in Machine Learning: From Beginner to Professional

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This course covers the basic concepts of machine learning (ML) that are crucial for getting started on the journey of becoming a skilled ML developer. You will become familiar with different algorithms and networks, such as supervised, unsupervised, neural networks, Convolutional Neural Network (CNN), and Super-Resolution Convolutional Neural Network (SRCNN), needed to develop effective ML solutions.

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67 on-demand videos & exercises
Level: Beginner & Intermediate
15hrs 26mins
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What to know about this course

From self-driving cars to artificial intelligence (AI) bots, machine learning (ML) is slowly spreading its reach and making our devices smarter. If you have ever wanted to play a role in the future of technology development, then here is your chance to get started with ML.

This course breaks the complex topics of ML into simple concepts that are easier to understand. The course starts with an introduction to ML, explaining its applications in the real-world and how it is different from AI. Next, you will learn supervised and unsupervised algorithms and understand the role of neural networks in ML. Once you understand the ML algorithms, you will dive into building interesting projects to consolidate your learning. You will learn how to build a board game review prediction model, how to build a credit card fraud detection model, how to tokenize word and sentences using natural language processing), how to build an object recognition model, how to build an image quality improvement model, how to build a text classification model, how to build an image analysis model, and how to build a data compression model. By the end of this course, you will have gained the skills to create real-world ML solutions.

Who's this course for?

If you want to understand machine learning (ML) algorithms and concepts to build effective ML solutions for the modern world, this course is for you.
Basic Python skills and a good understanding of mathematics are needed to get started with this course.

What you'll learn

  • Detect credit card fraud by using probability densities
  • Become familiar with the natural language processing methodology
  • Use the Canadian Institute for Advanced Research-10 (CIFAR-10) object recognition dataset to implement a deep neural network
  • Improve image quality using Super-Resolution Convolutional Neural Network (SRCNN)
  • Solve a text classification task using multiple classification algorithms
  • Use K-means clustering in an unsupervised algorithm.

Key Features

  • Grasp the core concepts of machine learning (ML).
  • Find out how to use neural networks in ML projects.
  • Learn how to build real-world projects using supervised and unsupervised learning algorithms.

Course Curriculum

About the Author

Eduonix Learning Solutions

Eduonix learning Solutions is a premier training and skill development organization which was started with a vision to bring world class training content, pedagogy and best learning practices to everyone's doorsteps . Eduonix aims to identify and provide the best learning and training environment. It identifies industry veterans and content creators around the globe and bring it to the global audience using number of intuitive platforms for easy and affordable access to quality content. Eduonix offers easy to understand online courses and workshops for everyday people. If you have ever wanted to learn a new skill, but don't want to attend four years of college to do it, we have a solution for you.

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