We know that technology tends to move in hype cycles, where certain topics and terminology are bandied around in press releases, news articles, research, and funding announcements. These include Blockchain, ICO, IoT, as well as AI, Machine Learning … 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.
The Rise of Machine Learning at the Network Edge
Over the past few months, I have shown you why machine learning at the network edge is so essential. In this final article, we look back at why machine learning is needed and look at some of the real-world cases where it has already been … Read more
The Future of Machine Learning at the Edge
Over the last few months, I have shown you how Machine Learning at the edge is improving our lives. I also shared some practical examples to give you a chance to try it for yourselves. In this article, I look at the current limitations of edge ML and … Read more
AI Ladder: the IBM Approach to Artificial Intelligence
TIME TO UPGRADE YOUR APPLICATION ESTATE?Tackle Modernization and Cloudification - on November 19th 2020, 10:00 am (GMT+1)The Cloud and AI Forum is an opportunity to learn how Italian Executive & Technical Leaders introduced data efficiency, … Read more
Questions and Answers in Virtual Assistants
The typical customer care virtual assistant (aka chatbot) can answer simple questions and maybe even perform some actions. But we need chatbots that really help solve customer problems instead of disappointing them with a “Sorry, I don't know.” When … Read more
Voice Control: Building Your Voice Assistant
Voice control was the stuff of science fiction throughout the 20th Century. But in the last two decades, voice control has entered the mainstream. Voice assistants like Siri and Alexa are embedded in home devices, headphones, and even … Read more
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
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
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
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 The use of chatbots is a fast-growing trend that meets the needs of all stakeholders. According to … Read more
Genetic Algorithms: A Developer’s Perspective
The life of a developer nowadays is a very exciting one: we have several languages, frameworks, and numerous excellent tools available to select from according to our needs. Not only that, we also have a lot of interesting and useful … 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
The cutting edge of real-time AI
Machine learning is traditionally processor-intensive; ML algorithms require large numbers of parallel operations. As a result, the models usually run in data centres at the core of the network. However, this has a direct impact in terms of latency, … Read more
AI-driven Conversational User Interface enriched with Search Skills
Today, chatbots are implemented almost everywhere, including many websites. The IBM Watson approach allows us to easily integrate AI features and deploy a web chatbot in just a few hours. In this article, we’ll put this in practice within IBM … Read more
TensorFlow Furthers the Development of Machine Learning
In preparation for his talk at the upcoming Codemotion Deep Learning virtual conference next week, I spoke to Luiz GUstavo (Gus) Martins, TensorFlow Developer Advocate, at Google. He explained that his main role is to help … Read more
How to teach Alexa to pronounce your name
Deep learning promises to deliver a true revolution in how we tackle complex problems. But to most people, deep learning seems like some arcane dark science. However, it is one of the key planks that enabled voice assistants, such as Alexa, to get so … Read more
How to build a GAN in Python
Introduction Generative Adversarial Networks (GANs) are a hot topic in machine learning for several good reasons. Here are three of the best: GANs can provide astonishing results, creating new things (images, texts, sounds, etc.) by imitating … Read more
IBM Think Digital 2020: AI for Enterprise and the Value of Language
IBM recently hosted Think Digital 2020, a series of fascinating talks, presentations and interviews all facilitated remotely during the COVID-19 stay at home order. The two-day event was an opportunity to discuss the state of business and the … Read more
Epidemic Intelligence, part 2: data, models and machine learning in the age of Coronavirus
In a previous article, we shared some reflections on machine learning models for data fitting and prediction, playing with a simple dataset related to the spread of the current coronavirus emergency. We looked at simple models and mentioned some … Read more