Brief Introduction
Learn the principles of machine learning and the importance of algorithms.
Description
Machine Learning is a growing field that is used when searching the web, placing ads, credit scoring, stock trading and for many other applications.
This data science course is an introduction to machine learning and algorithms. You will develop a basic understanding of the principles of machine learning and derive practical solutions using predictive analytics. We will also examine why algorithms play an essential role in Big Data analysis.
Knowledge
- What machine learning is and how it is related to statistics and data analysis
- How machine learning uses computer algorithms to search for patterns in data
- How to use data patterns to make decisions and predictions with real-world examples from healthcare involving genomics and preterm birth
- How to uncover hidden themes in large collections of documents using topic modeling
- How to prepare data, deal with missing data and create custom data analysis solutions for different industries
- Basic and frequently used algorithmic techniques including sorting, searching, greedy algorithms and dynamic programming
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Use Apache Flink and its ecosystem to process real-time big data Have you used Flink, but want to learn how to set it up and use it properly?...
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Programming Concept for high School Students Welcome to Python Crash Course! In this course we will learn about python fundamental and object oriented programming (python)....
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Your pipeline will first transform the dataset into BERT-readable features and store the features in the Amazon SageMaker Feature Store. Week 1: Feature Engineering and Feature Store...
