Daniel Lindsäth

Daniel Lindsäth has a diverse and extensive work experience in the technology industry. Daniel is currently employed as a Senior Software Developer at Edgeware AB since June 2018. Prior to this, they worked at FLIR Systems as a Middleware c from December 2017 to June 2018. Daniel also has experience as a Consultant at Zenterio Services from January 2016 to June 2018, and as a DRM systems integrator at Edgeware AB from March 2016 to December 2017. Before these roles, they worked as a Software Consultant at Zenterio AB from November 2015 to February 2016, and as a Consultant at Systemagic AB from February 2012 to December 2015. Daniel also has previous experience as an IPTV platform integrator at Ericsson from April 2012 to October 2015, and as a Software consultant at Zenterio AB from an unknown start date to March 2012. Daniel began their career as a Software Engineer at 27M Technologies from February 2007 to January 2012. Additionally, Daniel is a member of Vetenskap och Folkbildning since May 2012.

Daniel Lindsäth has a strong educational background in computer science and physics. Daniel obtained their M.Sc degree from Chalmers University of Technology in 2006, specializing in computer science and physics. Prior to that, they completed their B.Sc degree in computer science, maths, and physics from Karlstad University in 2004.

In addition to their formal education, Daniel has pursued various certifications related to machine learning and deep learning. Daniel obtained certifications from Coursera, including "Build, Train, and Deploy ML Pipelines using BERT", "Optimize ML Models and Deploy Human-in-the-Loop Pipelines", "Analyze Datasets and Train ML Models using AutoML", "Apply Generative Adversarial Networks (GANs)", "Custom Models, Layers and Loss Functions", "Build Better Generative Adversarial Networks (GANs)", "Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization", "Neural Networks and Deep Learning", "Structuring Machine Learning Projects", "Machine Learning", and "Neural Networks for Machine Learning". These certifications were obtained between 2017 and 2021, with the most recent one being in July 2021.

There is also mention of a certification in "Convolutional Neural Networks" from Coursera, but the specific month and year of obtaining this certificate are not provided.