September 7, 2022

By Natalia Cohn

August 3, 2022

By Natalia Cohn

Vertex AI + Kubeflow tutorial

Usually, taking a ML model from the experimentation environment to production consumes a huge amount of time and resources. Vertex AI makes it easy to train, deploy and compare model results. It is an excellent tool that allows us to focus on ML solutions rather than infrastructure management. In the following post, we will dive … Continued

Thinking of applying for a job at Marvik?

Who are we? Marvik is a hands-on machine learning consulting firm. We do tailor developments for companies who need to solve a complex problem using AI but can’t do it internally. This usually means they need results faster than it takes to build an internal team or just can’t get enough skilled people. This article … Continued

A summary of our 2021 and what’s next for 2022

We are almost at the end of a new year in Marvik. It was an excellent year, where the company grew a lot and we achieved many goals, but above all a year of personal and professional growth for the whole team, solving challenging technical problems and where we also had a lot of fun … Continued

When electronics meets machine learning

In this post we attempt to summarize the experience of working on a project that combines signal processing, machine learning and electronics. Its goal was to develop a manipulable sensor-embedded device from which to infer the kind of movement or activity performed by its user. By inference we mean the classification of the activity based … Continued

MLOps: Just DevOps for machine learning?

The following article tries to summarize what is exactly ML Ops and attempts to give a few guidelines for anyone trying to dive into it (or assess if you need to dive into it).    Let me start by saying that MLOps is just the new hype in AI. This has started as a set … Continued

Model distillation: leveraging lack of data with StyleGAN2

  In this blog we are going to talk about a technique called model distillation, and how can it be used to train supervised models from synthetic datasets created with GANs. With this technique, we can take advantage of the properties of unconditional image generation and use them in conditional models, with an outstanding improvement … Continued

How to optimize your model with TF-TRT for Jetson Nano

In this post we will grab a Tensorflow 2 model, optimize it with NVIDIA TensorRT, and deploy it for inference on a JetsonNano. First of all, is optimizing necessary? Short Answer: no. You might have reached to the conclusion that using TensorRT (TRT) was mandatory for running models on the Jetson Nano, this is however, … Continued

Speech synthesis and voice cloning

Speech synthesis literally means producing artificial human speech. It presents a lot of practical applications, such as music generation, text-to-speech conversion or navigation systems guidance. Traditional approaches for speech synthesis involved searching for speech units that match an input text on a large database and concatenate them to produce an audio file. It often resulted … Continued

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