Learning Highlights

Program Overview

Developers are worried about using various algorithms to solve different problems. This course is a perfect guide to identifying the best solution to efficiently build machine learning projects for different use cases to solve real-world problems. In this course, you will learn how to build a model that takes complex feature vector form sensor data and classifies data points into classes with similar characteristics. Then you will predict the price of a house based on historical data. Finally, you will build a Deep Learning model that can guess personality traits using labeled data. By the end of this course, you will have mastered each machine learning domain and will be able to build your own powerful projects at work.

Style and Approach

This is a step-by-step and fast-paced guide that will help you learn different ML techniques you can use to solve real-world problems, Every section will tackle a practical problem and take your ML skills to the next level

Course Outline
Learning Outcomes
 
  • The fundamentals of unsupervised learning algorithms and their importance
  • TensorFlow 2.0 terminology
  • Hands-on experience solving real-world problems in unsupervised learning
  • A practical approach to solving business problems, ranging from data preprocessing to model-building from a given dataset
Prerequisites
 
  • As the learning module is completely based on Java, the learners are expected to have a working knowledge of the Java programming language. Additionally, basic understanding of ML concepts is required to successfully complete this course. 

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