ML Metrics: Sensitivity vs. Specificity

, ,

In 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)

/0 Commentaires/par

Data Science vs. AI vs. ML vs. Deep Learning

, ,

Comparison 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:

  • Data architecture
  • In data acquisition
  • Data analysis
  • In data archiving

Learn more about Data Science.


Source de l’article sur DZONE (AI)

/0 Commentaires/par

Machine Learning in a Box (Week 6): SAP HANA R Integration

, ,

A 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)

/0 Commentaires/par

Beauty and the Monster: A Casual Story of Model Management

, ,

About 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)

/0 Commentaires/par

High-Accuracy Population-Based Image Search

, ,

Alibaba Machine Intelligence Technology Laboratory

Established in 2018, the Machine Intelligence Technology Laboratory comprises of a group of outstanding scientists and engineers, with research centers located in Hangzhou, Beijing, Seattle, Silicon Valley, and Singapore. Machine Intelligence Technology Laboratory is Alibaba’s core team responsible for the research and development of artificial intelligence technologies. Relying on Alibaba’s valuable massive data and machine learning/deep learning technologies, the lab has developed image recognition, speech interaction, natural language understanding, intelligent decision-making, and other core artificial intelligence technologies. It fully empowers Alibaba Group’s important businesses such as e-commerce, finance, logistics, social interaction, and entertainment, and also provides outputs to ecosystem partners to jointly build a smart future.

Image Search

Image title


Source de l’article sur DZONE (AI)

/0 Commentaires/par

Training TensorFlow Object Detection Models

, ,

TensorFlow Object Detection is a powerful technology that can recognize different objects in images, including their positions. The trained Object Detection models can be run on mobile and edge devices to execute predictions very quickly. I’ve used this technology to build a demo where Anki Overdrive cars and obstacles are detected via an iOS app. When obstacles are detected, the cars are stopped automatically.

Check out the short video (only 2 mins) for a quick demo.


Source de l’article sur DZONE (AI)

/0 Commentaires/par

AI and the Online Job Market

, ,

If you’ve spent any time job hunting, you’ll no doubt be well aware of how frustrating and hopeless the task can seem at times.

The haphazardous process of getting yourself noticed in a sea of applications that may be prioritized despite carrying less relevance is tricky enough. But then you may find that when you eventually do accept a role, it’s nothing like you were led to believe it would be.


Source de l’article sur DZONE (AI)

/0 Commentaires/par

GAN Lab: Generated Adversarial Networks In Your Browser!

, ,

This GitHub project is a highly interactive graphic demonstration of the features and operations of a generated adversarial network using TensorFow.js. It is based on work done by Minsuk Kahng, Nikhil Thorat, Duen Horng (Polo) Chau, Fernanda B. Viegas, and Martin Wattenberg in their paper: GAN Lab: Understanding Complex Deep Generative Models using Interactive Visual Experimentation.

Full disclosure: The data sets are small enough and simple enough to demonstrate the technology but clearly are not full-blown image processing examples, which can often consume a lot (CPU/years?) of computer time. But these small examples provide an excellent introduction into what is going on. It takes away the spooky magic…which is a good thing! 


Source de l’article sur DZONE (AI)

/0 Commentaires/par

[DZone Research] Popular AI Algorithms and Their Uses

, ,

This article is part of the Key Research Findings from the DZone Guide to Artificial Intelligence: Automating Decision-Making.

Introduction

As part of the research for our 2018 Guide to Artificial Intelligence, we surveyed 403 developers, data scientists, and technologists. From their responses, we’ve created a quick article on the different algorithms available for working with various AI projects, and which one proved more popular.


Source de l’article sur DZONE (AI)

/0 Commentaires/par

Use Case: AI and the KYC Industry

, ,

Tech companies around the globe have started integrating Artificial Intelligence (AI) into their products for faster processing and substantially reduced manual work. Whether it is search engine results from Google or Siri from Apple, AI has been utilized with perfection by multiple industries to streamline their business practices for better service delivery. However, there are still various tech sub-industries and niches that can take help from AI to finely tune their products and come up with even more customer friendly services. Know Your Customer, also known as KYC, the industry has a lot to benefit from Artificial Intelligence. More and more businesses are being subjected to regulations that require these businesses to carry out full proof KYC verification with the help of an official identity document before a customer is registered. It is high time that AI becomes a cornerstone for KYC software industry for improving the standards of service in this field.

What Is KYC?

As explained above, KYC stands for Know Your Customer. It is a business practice that is conducted before any product is sold or service is utilized by an end-user. The service provider is required to collect comprehensive personal information from their customers. Verifying those credentials is the responsibility of the company that is collecting information from their customers. Most of the times, an official identity document is used to confirm the identity details of a customer. What aspects of a person’s identity are verified, depends on the regulatory guidelines or the nature of business performing a KYC verification.


Source de l’article sur DZONE (AI)

/0 Commentaires/par