For many, gazing at an old photo of a city can evoke feelings of both nostalgia and wonder. We have Google Street View for places in the present day, but what about places in the past? What was it like to walk through Manhattan in the 1940s? To … Read more
Machine Learning Developer
The Machine Learning Developer is specialized in integration of machine learning and Artificial Intelligence into tools and apps. He is able to develop, customize and optimize learning algorithms.
The main requirements of a Machine Learning Developer are:
deep knowledge of languages such as Python and C ++, experience in the implementation of algorithms in Computer Vision and Machine Learning (Deep Learning), knowledge of object- oriented programming, data-parallel processing and/or GPU programming with CUDA and OpenCL.
Find job offers in Job Search for Machine Learning Developer.
Seeing is believing: image recognition on a €10 MCU
This series is exploring the rationale for moving machine learning to the network edge. This article looks in more detail at image recognition, one of the prime use cases for ML at the edge. As explained in previous articles, there are many use … Read more
Exploring LIME Explanations and the Mathematics Behind it
The expansion of artificial intelligence (AI) relies on trust. Users will reject machine learning (ML) systems they cannot trust. We will not trust decisions made by models that do not provide clear explanations. An AI system must provide clear … Read more
Using deep learning to control the unconsciousness level of patients in an anesthetic state
In recent years, researchers have been developing machine learning algorithms for an increasingly wide range of purposes. This includes algorithms that can be applied in healthcare settings, for instance helping clinicians to diagnose specific … Read more
14 open source tools to make the most of machine learning
Spam filtering, face recognition, recommendation engines — when you have a large data set on which you’d like to perform predictive analysis or pattern recognition, machine learning is the way to go. The proliferation of free open source software has … Read more
Finally a way to make money out of quantum: selling randomness
A UK-based quantum software startup has today announced the roll-out of a certifiably quantum, cloud-based random number generation service. The news by Cambridge Quantum Computing reported by Sifted may seem esoteric but it’s important for the … Read more
How to make complicated machine learning developer problems easier to solve
We sometimes assume the best software companies will yield the best artificial intelligence but, as Andreessen Horowitz investors Martin Casado and Matt Bornstein argue in their post about AI economics, this isn't necessarily the case. In fact, "...a … Read more
‘Selfies’ could be used to detect heart disease: new research uses artificial intelligence to analyse facial photos
Sending a “selfie” to the doctor could be a cheap and simple way of detecting heart disease, according to the authors of a new study published in the European Heart Journal. The study, reported by Escardio, is the first to show that it’s possible … Read more
ML at the Edge: a Practical Example
Machine learning is the primary methodology for delivering AI applications. In previous articles, I discussed the main reasons behind moving machine learning to the network edge. These include the need for real-time performance, security … Read more
The problems AI has today go back centuries
In March of 2015, protests broke out at the University of Cape Town in South Africa over the campus statue of British colonialist Cecil Rhodes. Rhodes, a mining magnate who had gifted the land on which the university was built, had committed genocide … Read more
Google AI Hub: what, why, how
Artificial intelligence (AI) and machine learning (ML) increasingly seem to be indispensable tools that developers need to be able to handle. There are many ways these tools can be put to use, applied to applications and products. In research and … Read more
NTT invents distributed machine learning for the edge
Japanese heavyweight NTT has come up with a way to carry out coordinated machine learning on multiple edge servers. As reported by Telecoms.com, it is similar to a blockchain or an artificial neural network, in that it is essentially a consensus … Read more
Why the nonprofit OpenAI made GPT-3 a commercial product
A program that can automate website development. A bot that writes letters on behalf of nature. An AI-written blog that trended on Hacker News. Those are just some of the recent stories written about GPT-3, the latest contraption of artificial … Read more
Conversational AI Is the New UX
Table Of ContentsTargeting the Internet of ThingsForget the past: you need a new mindsetAPI-based multi-channel AI solutionsTalking to the user ¡Hispanohablantes esto es para vos!ONLINE MULTI-TRACK CONFERENCE Un solo boleto para asistir a cuatro … Read more
Amazon Releases Quantum Computing Service Braket into General Availability
Amazon Braket is a fully-managed AWS service that provides a development environment for exploring and designing novel quantum algorithms. With the service, customers can test and troubleshoot their algorithms on quantum circuit simulators and run … Read more
Genetic Algorithms: A Developer’s Perspective
¡Hispanohablantes esto es para vos!ONLINE MULTI-TRACK CONFERENCE Un solo boleto para asistir a cuatro conferencias dentro de un mismo evento, sobre Backend, Frontend, Emerging Technologies, AI/ML/DL. Las mejores tecnologías, actividades, buenas … Read more
MLops: The rise of machine learning operations
As hard as it is for data scientists to tag data and develop accurate machine learning models, managing models in production can be even more daunting. Recognizing model drift, retraining models with updating data sets, improving performance, … Read more
How AI and IIoT Are Making the Auto Industry More Aware
Nothing good tends to come from something that is broken. It’s bad enough to have to deal with problems in the factory: The average manufacturer deals with around 800 hours of downtime annually, which translates to almost $1 million in lost … Read more
Edge computing and AI: 7 things to know
For decades, artificial intelligence (AI) lived in data centers, where there was sufficient compute power to perform processor-demanding cognitive tasks. In time, AI made its way into software, where predictive algorithms changed the nature of how … Read more
Getting started with edge machine learning
In this six-article series from Mouser Electronics, we explore why AI is moving to the network edge and the technology that’s making it possible. The first article examined why AI needs to move to the edge. Here, we dive in to the hardware and tools … Read more
