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Processing of Space Monitoring Information (Coursera)

Observation of near-Earth outer space is an important task for astronomers and scientists at the present time. This task is to determine the coordinate and non-coordinate characteristics of artificial space objects. According to data obtained, a catalogue of objects is created, which should be maintained and updated. For this, [...]
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Cluster Analysis, Association Mining, and Model Evaluation (Coursera)

Welcome to Cluster Analysis, Association Mining, and Model Evaluation. In this course we will begin with an exploration of cluster analysis and segmentation, and discuss how techniques such as collaborative filtering and association rules mining can be applied. We will also explain how a model can be evaluated for [...]
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Advanced Recommender Systems (Coursera)

Sep 27th 2021
Advanced Recommender Systems (Coursera)
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In this course, you will see how to use advanced machine learning techniques in order to build more sophisticated recommender systems. Machine Learning is able to provide recommendations and make better predictions, by taking advantage of historical opinions from users and building up the model automatically, without the need [...]
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Nearest Neighbor Collaborative Filtering (Coursera)

In this course, you will learn the fundamental techniques for making personalized recommendations through nearest-neighbor techniques. First you will learn user-user collaborative filtering, an algorithm that identifies other people with similar tastes to a target user and combines their ratings to make recommendations for that user. [...]
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Data Analysis Using Python (Coursera)

This course provides an introduction to basic data science techniques using Python. Students are introduced to core concepts like Data Frames and joining data, and learn how to use data analysis libraries like pandas, numpy, and matplotlib. This course provides an overview of loading, inspecting, and querying [...]
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Basic Recommender Systems (Coursera)

This course introduces you to the leading approaches in recommender systems. The techniques described touch both collaborative and content-based approaches and include the most important algorithms used to provide recommendations. You'll learn how they work, how to use and how to evaluate them, pointing out benefits and limits of [...]
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Digital Signal Processing 2: Filtering (Coursera)

Digital Signal Processing is the branch of engineering that, in the space of just a few decades, has enabled unprecedented levels of interpersonal communication and of on-demand entertainment. By reworking the principles of electronics, telecommunication and computer science into a unifying paradigm, DSP is a the heart of the [...]
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Introduction to Data Analysis Using Excel (Coursera)

The use of Excel is widespread in the industry. It is a very powerful data analysis tool and almost all big and small businesses use Excel in their day to day functioning. This course is designed to give you a working knowledge of Excel with the aim of getting [...]
5
Average: 5 ( 4 votes )

Introduction to Recommender Systems: Non-Personalized and Content-Based (Coursera)

This course, which is designed to serve as the first course in the Recommender Systems specialization, introduces the concept of recommender systems, reviews several examples in detail, and leads you through non-personalized recommendation using summary statistics and product associations, basic stereotype-based or demographic recommendations, and content-based filtering recommendations. [...]
6
Average: 6 ( 4 votes )

Technology Commercialization, Part 1: Setting up your Idea Filtering System (Coursera)

Sep 13th 2021
Technology Commercialization, Part 1: Setting up your Idea Filtering System (Coursera)
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New ideas based on high-technology research have a high failure rate because they hit the ground running with lopsided priorities and misalignments. Students complete this course with an Innovation Creed (“Why are you doing this?”) and a customized Idea Filter (“Are you working on the right priorities?”)—2 simple tools [...]
3
Average: 3 ( 3 votes )