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ML Metrics: Sensitivity vs. Specificity
Actualités, Développement IoT, InnovationIn this post, we will try and understand the concepts behind evaluation metrics such as sensitivity and specificity, which is used to determine the performance of the Machine Learning models. The post also describes the differences between sensitivity and specificity. The concepts have been explained using the model for predicting whether a person is suffering from a disease or not.
What Is Sensitivity
Sensitivity is a measure of the proportion of actual positive cases that got predicted as positive (or true positive). Sensitivity is also termed as Recall. This implies that there will be another proportion of actual positive cases, which would get predicted incorrectly as negative (and, thus, could also be termed as the false negative). This can also be represented in the form of a false negative rate. The sum of sensitivity and false negative rate would be 1. Let’s try and understand this with the model used for predicting whether a person is suffering from the disease. Sensitivity is a measure of the proportion of people suffering from the disease who got predicted correctly as the ones suffering from the disease. In other words, the person who is unhealthy actually got predicted as unhealthy.
Source de l’article sur DZONE (AI)
Project Management Techniques and Tools Made Simple
Développement applicatif, Méthodes et organisation des process ITChoosing the right approach to managing a project is crucial for successful project delivery. The way you manage work is defined by techniques that you use and the tools that you adopt. In this article, we’ve collected project management tools and techniques that are used in different fields and help create an efficient process.
Project Management Techniques
Techniques in project management range from traditional to innovative ones. Which one to choose for running a project depends on project specifics, its complexity, teams involved, and other factors. Most of them can be used in various fields, however, there are techniques that are traditionally used in certain areas of activity, or are developed specifically for certain fields. Below, we’ve listed the most popular techniques that are used in project management.
Source de l’article sur DZone (Agile)
Making Scala Faster: Three Expert Tips for Busy Dev Teams [Video and Slides]
Actualités, Méthodes et organisation des process ITHow To Make Your Scala Applications Compile Faster
With Scala, JVM developers get a host of benefits over other programming languages. From code conciseness (fewer LOC) and native scalability to support for functional programming paradigms and type safety, Scala is the language of choice for modern enterprises like Amazon, HPE, PayPal, and Walmart.
Source de l’article sur DZONE
Data Science vs. AI vs. ML vs. Deep Learning
Actualités, Développement IoT, InnovationComparison Between Data Science, AI, ML, and Deep Learning
What Is Data Science?
R Data science includes data analysis. It is an important component of the skill set required for many jobs in this area. But it’s not the only necessary skill. They play active roles in the design and implementation work of four related areas:
Learn more about Data Science.
Source de l’article sur DZONE (AI)
Machine Learning in a Box (Week 6): SAP HANA R Integration
Actualités, Développement IoT, InnovationA Quick Recap
Last time, we looked at how to import data in SAP HANA express, and we used the dataset provided by the SAP Predictive Analytics tools (and available online).
But the main idea was to show you how you can import more or less any kind of text/CSV files in your HXE instances.
Source de l’article sur DZONE (AI)
Beauty and the Monster: A Casual Story of Model Management
Actualités, Développement IoT, InnovationAbout a year ago, we told a beautiful story about how KNIME Analytics Platform can be used to automate an established modeling process using the KNIME Model Factory. Recently, our Life Science team faced an exhausting and frightening exercise of building, validating, and scoring models for more than 1500 data sets.
We want to share with you how we adapted the KNIME Model Factory for this monstrous application. We hope this will show you how to implement your own model building routines in the KNIME Model Factory. We will also demonstrate how to scale model building processes to very large tasks using KNIME Server Distributed Executors.
Source de l’article sur DZONE (AI)
Code Review
Actualités, Méthodes et organisation des process ITI can’t actually share all the code. So this feels incomplete. But I can share what I said about the code. Then you can look at your code and decide if you’ve got similar problems to fix.
My responses were these. I’ll expand on them below.
Source de l’article sur DZONE
Python 101: Episode #25: Decorators [Video]
Actualités, Méthodes et organisation des process ITIn this episode, you will learn the basics of Python decorators and what the are good for.
You can read the chapter this screencast is based on here: http://python101.pythonlibrary.org/ or purchase the book on Leanpub
Source de l’article sur DZONE
How to Expedite the Creation of JUnit Parameterized Tests
Actualités, Méthodes et organisation des process ITWhen writing unit tests, it is common to initialize method input parameters and expected results in the test method itself. In some cases, using a small set of inputs is enough; however, there are cases in which we need to use a large set of values to verify all of the functionality in our code. Parameterized tests are a good way to define and run multiple test cases, where the only difference between them is the data. They can validate code behavior for a variety of values, including border cases. Parameterizing tests can increase code coverage and provide confidence that the code is working as expected.
There are a number of good parameterization frameworks for Java. In this article, we will look at three different frameworks commonly used with JUnit tests, with a comparison between them and examples of how the tests are structured for each. Finally, we will explore how to simplify and expedite the creation of parameterized tests.
Source de l’article sur DZONE
Change Streams With MongoDB
Actualités, Méthodes et organisation des process ITMongoDB is always one step ahead of other database solutions in providing user-friendly suplog port with advance features rolled out to ease operations. The OpLog feature was used extensively by MongoDB connectors to pull out data updates and generate stream. OpLog feature banked on MongoDB’s internal replication feature. While the feature was highly useful, it was complex and necessarily mean tailing of logs.
To simplify things, Change Streams as subscriber to all insert, update, delete MongoDB collection operations was introduced, which should go well with Node.js event-based architecture.
Source de l’article sur DZONE